bio europe 2026: ERS Respiratory Precision Therapy Guide

ERS 2026 Preview: Before Precision Respiratory Therapy Can Move Toward Single-Use Interventions, Challenges in Delivery and Long-Term Safety Must Be Overcome

 From September 5 to 9, 2026, the **European Respiratory Society International Congress 2026 (ERS International Congress 2026)** will be held in Barcelona, Spain.This global academic and clinical gathering in the field of respiratory medicine, which typically attracts approximately 20,000 delegates, will focus in 2026 on the collaboration among patients, clinicians, and researchers. While bio europe 2026 draws the broader biotech industry for partnering, the scale of the event alone is not a definitive indicator; the real question is: with biologics, nucleic acid therapeutics, mRNA, small molecules, and immunotherapy all on the agenda, has precision therapy in respiratory medicine truly become part of routine clinical decision-making, or does it remain confined to isolated research cases?

 In vivo gene editing achieved its first positive Phase III result in 2026. Intellia Therapeutics’ Lonvo-z, used to treat hereditary angioedema, demonstrated in Phase III data a reduction in attack frequency of approximately 87%, becoming the world’s first in vivo CRISPR therapy to succeed in Phase III clinical trials. This advancement has transformed the “one-time intervention” from a concept into a verifiable product.However, respiratory diseases differ from HAE. Directly extrapolating success in other indications to the respiratory system obscures the questions that truly need to be answered: Can editing tools or drugs reach the correct respiratory cells, produce a controllable and sustained effect, and establish a scalable, quality-controlled manufacturing pathway?

 This article focuses on macromolecular biologics, nucleic acid therapeutics and mRNA, small molecules, and immunotherapy—key topics on the ERS 2026 agenda—and uses advances in in vivo gene editing (CGT) as a frame of reference to assess how far precision therapy for respiratory diseases remains from real-world clinical application. The criteria for evaluation lie not in the novelty of the technology, but in four key factors: identifying the right patients, reaching the right cells, maintaining a controllable effect, and establishing a manufacturable pathway.

 1. From bio europe 2026 to ERS: What makes ERS 2026 worth watching is not the number of new technologies, but whether precision therapy can be integrated into real-world respiratory care

 The high heterogeneity of respiratory diseases is a prerequisite for any discussion of precision therapy. Chronic obstructive pulmonary disease (COPD), asthma, idiopathic pulmonary fibrosis, pulmonary arterial hypertension, cystic fibrosis, and α1-antitrypsin deficiency—these diseases, all categorized under “respiratory,” differ in their pathophysiological mechanisms, patient subtypes, affected cells, and degree of reversibility.The more advanced the technology, the more it must answer a fundamental question: Can it identify the right patients and improve long-term respiratory outcomes? If each new technology is treated merely as a standalone highlight, European biotech partnering conferences risk missing the true clinical picture.

 Table 1.1 Comparison of Decision-Making Dimensions in Respiratory Therapy: From Broad-Spectrum Management to Molecular Stratification

Dimension	Broad-Spectrum Control Era	Molecular Stratification Era	Basis for Judgment
Treatment Goals	Control symptoms and reduce acute exacerbations	Modify or block specific pathogenic pathways	Can it cover more mechanistic subtypes?
Patient Selection	Based on lung function and symptom scores	Based on biomarkers, genotypes, and imaging phenotypes	Is the classification predefined and independently validated?
Efficacy Evaluation	Improvement in FEV1, number of acute exacerbations	Target cell editing rate, biomarker changes, PRO	Does improvement in these metrics translate into perceptible benefits?
Route of administration	Inhalation, oral, intravenous	Inhaled LNP, systemic delivery, in vivo editing	Does the delivery reach the target cells?
Safety Profile	Acute Adverse Events, Drug Interactions	Off-target effects, immunogenicity, long-term monitoring	Reversibility and modulability
Manufacturing Pathways	Standardized Small Molecules/Biologics	Personalized or platform-based CGT	Batch-to-batch consistency and scalability

 The table above is not a diagram illustrating a replacement of old technologies with new ones, but rather a decision-making framework. A single patient may require both broad-spectrum control and molecularly stratified therapy simultaneously; the key lies in determining which type of technology can address the core issues of the current disease stage. Equating “advanced” with “priority” would marginalize small molecules and immunotherapy—which are suitable for long-term management—and place clinical expectations on in vivo editing, which is still in the early stages of validation, that exceed its capabilities.

 1.1 The Shift from Broad-Spectrum Control to Molecular Stratification: A Change in Treatment Decision-Making

 From large-molecule biologics, nucleic acid drugs and mRNA, small molecules, to immune-targeted therapies, these four categories of technologies should not be ranked by age but compared across four dimensions: disease mechanisms, patient subtypes, sites of action, and treatment goals.The efficacy of biologics for type 2 inflammatory asthma has been established, but type 2 inflammation itself comprises multiple subtypes, and biomarkers such as peripheral blood eosinophil count, FeNO, and periosteal protein levels carry different weights in predicting treatment response. Nucleic acid drugs and mRNA therapies are currently being validated primarily for rare diseases and specific monogenic disorders, with delivery for respiratory indications remaining a bottleneck.Oral or inhaled small molecules have inherent advantages in terms of adherence and accessibility, but exposure control, long-term safety, and resistance management require ongoing monitoring. Immune-targeted therapies require a delicate balance between inflammation control and infection risk.

 Table 1.2: The Role of Four Technology Categories and In Vivo Editing in Precision Respiratory Therapy

Technology Category	Mechanism of Action	Current Stage	Major Bottlenecks in the Respiratory Field
Biologics (monoclonal antibodies, etc.)	Type 2 inflammation, IgE, IL-5/IL-4Rα pathways	Multiple products already on the market; subgroup differentiation underway	Defining effective patient populations, post-treatment persistence, and long-term safety
Nucleic acid therapeutics (ASO/siRNA)	Monogenic diseases, silencing of specific signaling pathways	Focus on rare diseases first; early-stage respiratory applications	Pulmonary delivery, cell-targeted delivery, repeated dosing
mRNA	Protein replacement, vaccines, delivery of editing tools	Vaccines are mature; therapeutic mRNA is in the early stages	LNP Tissue selectivity, duration of expression
Small molecules	Multi-pathway modulability	Widespread use, iterative development of new targets	Long-term safety, drug resistance, and real-world adherence
Immunotherapy	Inflammation-Immunity Interface Pathways	Already on the market for certain indications	Risk of infection, balancing inflammation control
In vivo gene editing (CGT)	Correction of disease-causing genes	Phase III positive (HAE); respiratory indications to be validated	Delivery, off-target effects, long-term monitoring, CMC

 From a decision-making perspective, the real shift is that when faced with a specific patient, physicians no longer ask first, “Which class of drugs should be used?” but rather, “Which pathway drives this patient’s disease, which cells are involved, and what is the treatment goal?” This shift in sequence means that the focus of the conference should not be limited to “new data on a particular target,” but rather on whether the data addresses these three questions: pathway selection, cellular localization, and treatment goals.

 1.2 Patient Engagement Is Not Just a Conference Slogan, but a Calibrator for Endpoint Design

 The 2026 ERS Congress theme places patient engagement prominently, and this should not be viewed merely as a conference slogan. At the level of endpoint design, the practical role of patient engagement is to align study endpoints with what patients truly care about.Changes in lung function (FEV1) and biomarkers are objective measures, but the frequency of acute exacerbations, daytime symptoms, functional capacity, treatment burden, and quality of life are what patients experience on a daily basis. If improvements in technical indicators do not translate into benefits that patients can perceive, the product’s value remains incomplete.

 Table 1.3 Classification of Respiratory Clinical Study Endpoints and Patient Perception

Endpoint Category	Typical Measures	Clinical Significance	Patient Perception
Lung Function	FEV1, FVC, FEV1/FVC	Degree of airflow limitation	Indirect; requires spirometry
Biomarkers	Eosinophils, FeNO, periosteal protein, IgE	Activation status of signaling pathways	Not directly detectable; requires blood or exhaled breath testing
Acute Exacerbations	Number of acute exacerbations per year, number of hospitalizations, corticosteroid use	Disease stability, utilization of medical resources	High; directly impacts daily activities
Symptoms	ACT, ACQ, SGRQ, CAT	Control of daily symptoms	High; noticeable in daily life
Functional Ability	6-Minute Walk Distance, mMRC	Exercise Tolerance	High, quantifiable
Treatment Burden	Dosage frequency, number of clinic visits, out-of-pocket costs	Long-term acceptability	High, affects adherence
Quality of life	SGRQ, AQ20, PAQLQ	Overall Perception of Health	High, comprehensively reflecting

 Including endpoints with high patient-reported value as primary or secondary endpoints is the minimum standard for determining whether a study truly serves patients. Taking biologics as an example, if a Phase III study reports only improvements in FEV1 as its primary endpoint, without reporting reductions in acute exacerbations or improvements in PROs, the practical value of its conclusions will be diminished.The same logic applies to nucleic acid therapeutics and in vivo editing: editing rates and expression levels are mechanism-based indicators, but what patients ultimately care about is whether acute exacerbations can be reduced, whether long-term medication use can be minimized, and whether they can resume their daily activities. The benchmark for endpoint design is patient involvement.

 The action recommendation for this section is: When reading any study abstract from ERS 2026, first check whether the primary endpoint includes patient-perceived measures, then verify whether the secondary endpoints cover acute exacerbations, symptoms, and quality of life. If a study reports only mechanism-based measures, it should be classified as mechanism validation rather than clinical decision-making evidence, and further evaluation should await subsequent translational data.

 2. As biologics enter the next phase, the key is to define the target population more precisely

 The use of biologics in respiratory diseases has moved beyond the “proving efficacy” phase and entered the “proving who benefits most” phase. When discussing monoclonal antibodies and other macromolecules, simply listing targets one by one is no longer particularly meaningful; the focus should shift to how baseline biomarkers, comorbidities, prior treatments, and history of acute exacerbations collectively determine patient benefit.Key questions to explore at the conference include: whether efficacy persists after discontinuation or dose reduction, whether long-term safety signals are clear, and whether there are clear pathways for patients with low responsiveness.

 Clinical decision-making regarding biologics is shifting from a “try-and-see” approach to a “calculate-and-decide” approach. Baseline eosinophil levels, FeNO, periostin, IgE, the number of previous acute exacerbations, dependence on oral corticosteroids, and the presence of nasal polyps or atopic dermatitis collectively form a matrix for predicting treatment efficacy. Reducing these factors to a single threshold would result in the loss of a significant amount of predictive information.

 Table 2.1 Matrix of Baseline Factors for Predicting Biologic Efficacy

Baseline Factors	Common Thresholds/Ranges	Predictive Value	Usage Considerations
Peripheral Blood Eosinophils	≥150/μL or ≥300/μL	Prediction of Efficacy of Anti-IL-5 and Anti-IL-4Rα Therapies	Thresholds may vary depending on the time of testing and concomitant medications
FeNO	≥20 ppb or ≥50 ppb	Type 2 inflammation and efficacy of anti-IgE/anti-IL-4Rα	Affected by ICS dosage and infection
Periosteal protein	Elevated	Secondary marker of Type 2 inflammation	Test standardization varies
Total IgE	Elevated	Efficacy of anti-IgE therapy	Must be considered in conjunction with body weight and allergens
History of acute exacerbations	≥2 episodes/year	Intensity of treatment need	Definitions must be standardized
Dependence on oral corticosteroids	Required	Severe phenotype	Tapering Safety requires monitoring
Concomitant nasal polyps	Present	Enhanced benefit with anti-IL-4Rα and anti-IL-5	CRSwNP may increase the likelihood of Type 2 inflammation

 The key message from the table above is that a single threshold (e.g., eosinophils ≥ 300/μL) is insufficient for effective patient stratification; a combination of multiple factors is required.The “try for three months then reassess” strategy commonly used in clinical practice essentially infers phenotype based on treatment response; however, this approach delays appropriate treatment and exposes low-response patients to unnecessary immunosuppression. Refining the baseline matrix is a prerequisite for more accurately identifying the responsive population.

 2.1 Average Efficacy May Mask the True High-Benefit Subgroup

 The average efficacy reported in a Phase III study is often a weighted average of responses across different subgroups. If both high-benefit and low-benefit subgroups coexist, the average will simultaneously overestimate the expected response in the low-response subgroup and underestimate the potential of the high-response subgroup.When reviewing subgroup data, three questions must be addressed: Was the subgroup pre-specified (rather than a post-hoc analysis)? Is the sample size sufficient to support independent conclusions? Has the cutoff value been confirmed using an independent validation set? It is a fundamental rule that exploratory biomarkers cannot be directly adopted as clinical selection criteria.

 Table 2.2 Levels of Evidence and Limits of Application for Subgroup Analysis

Subgroup Type	Sample Size Requirements	Validation Requirements	Common Misconceptions
Predefined Subgroups	Sufficient to Support Independent Tests	Predefined in the protocol	Treating post-hoc subgroup analysis as pre-specified
Post-hoc Subgroups	Usually insufficient	Requires validation in an independent cohort	Used directly for clinical decision-making
Exploratory biomarkers	Usually insufficient	Requires confirmation through translational research	Formulated as selection criteria
Markers validated by independent studies	Sufficient	Multicenter independent validation	Threshold Extrapolation across populations
Real-world subgroups	Large sample size but high bias	Requires prospective data collection	Mistaking correlation for causation

 At ERS meetings, whenever you encounter a subgroup analysis, the first step is to confirm whether it was pre-specified or post-hoc. If a pre-specified subgroup is clearly defined in the protocol and the order of tests is predetermined, the conclusions can guide clinical decision-making. Post-hoc subgroups can only serve as hypotheses for future studies and should not be used as a basis for prescribing. Presenting post-hoc analyses as “new findings” is a common practice in conference presentations and should be viewed with caution.

 Action Recommendations for This Section: When reviewing subgroup data for biologics, first check whether the study protocol predefined the subgroups and the order of statistical tests; then verify whether the sample size is sufficient and whether the findings have been validated in an independent cohort. If either criterion is not met, classify the data as hypothesis generation and do not incorporate it into clinical pathways.

 2.2 Competition Among Large-Molecule Drugs Cannot Ignore the Burden of Administration and Long-Term Management

 The treatment cycle for chronic respiratory diseases spans years; administration frequency, feasibility of home use, immunogenicity, cold-chain requirements, discontinuation rates, and long-term follow-up—each of these factors determines whether patients can continue treatment. Significant efficacy must be evaluated in conjunction with patients’ ability to adhere to treatment over the long term; otherwise, the real-world transferability of efficacy data will be overestimated.

 Table 2.3 Evaluation Dimensions for Long-Term Management of Biologics

Management Dimensions	Impact Dimensions	Clinical Issue	Field Follow-Up Questions
Dosage Frequency	Adherence, Burden of Medical Visits	Differences between every 2 weeks, every 4 weeks, and every 8 weeks	Are there data on extended dosing intervals?
Route of administration	At home vs. in the hospital	Is subcutaneous injection suitable for home use?	Safety data for home use
Immunogenicity	Diminished Efficacy, Hypersensitivity Reactions	Incidence of Antibodies Against the Drug	Effect of ADA on PK/PD
Cold Chain and Storage	Accessibility, Cost	Storage requirements at 2–8°C	Room-Temperature Stability Data
Discontinuation Strategy	Long-term Safety and Financial Burden	Can treatment be discontinued after remission?	Recurrence Rate After Discontinuation
Long-term follow-up	Rare Adverse Events	Safety data for 5 years or more	Has a registry been established?
Cost and Accessibility	Real-world use	Self-payment and Reimbursement Coverage	Regional Disparities in Access

 It is a common misconception to equate the “long-acting” nature of biologics with “low burden.”The patient burden differs significantly depending on whether a biopharmaceutical is administered via subcutaneous injection every two weeks in a hospital setting or at home; efficacy decline due to immunogenicity may not become apparent until 6–12 months later; and cold-chain requirements in remote areas can result in inaccessibility. These factors collectively paint a true picture of the “long-term management burden,” yet conference reports typically focus solely on efficacy data, with insufficient discussion of the burden.

 Action recommendations for this section: When evaluating data on a biologic, in addition to efficacy metrics, verify at least five factors: dosing frequency, route of administration, immunogenicity, discontinuation strategies, and long-term follow-up. If any of these data points are missing, they should be marked as “to be supplemented” and not included in clinical decision-making. For chronic respiratory diseases, long-term acceptability is a prerequisite for efficacy.

 3. The First Hurdle for Nucleic Acid Drugs and mRNA Remains Reaching the Correct Cells

 When discussing the application of nucleic acid therapeutics (ASO, siRNA) and mRNA in respiratory drug development, delivery must be addressed before the mechanism of action.No matter how sophisticated the mechanism, if the nucleic acid or mRNA cannot reach the target respiratory cells, the mechanism remains confined to in vitro settings. Mature experience has been accumulated with liver-targeted LNP technology; Onpattro (patisiran) for transthyretin amyloidosis is a classic example. However, the success of liver targeting cannot be simply replicated across all respiratory indications.The lungs present challenges such as mucus barriers, diverse cell types, an inflammatory environment that affects delivery efficiency, varying endosomal escape efficiency, uneven dose distribution, and immune responses to repeated dosing—each of which constitutes a distinct delivery hurdle.

 Table 3.1 Barriers and Challenges for Nucleic Acid Drugs/mRNA at Different Delivery Sites

Delivery Site	Major Barriers	Technology Maturity	Challenges for Respiratory Indications
Liver (Systemic Administration)	Plasma stability, hepatic uptake	Mature (e.g., Onpattro is already on the market)	Does not directly address lung disease
Lung (inhalation)	Mucus, ciliary clearance, macrophage phagocytosis	Early-stage, limited clinical	Deposition distribution, patient inspiratory dependence
Airway epithelium	Mucus layer thickness, inflammatory exudate	Early stage	Changes in the disease state of the barrier
Alveolar epithelium	Surfactant, blood-air barrier	Early	Dose distribution and systemic leakage
Immune Cells (Intra-pulmonary)	Selective cellular uptake	Under investigation	Difficulty in targeting specific subpopulations
Systemic administration Targeting the lungs	Tissue selectivity, dose limitations	Research stage	Insufficient tissue selectivity of LNPs

 The table above shows that there is no “one-size-fits-all” solution for respiratory delivery. The success of hepatic LNPs relies on hepatic sinusoidal permeability and ApoE-mediated uptake, whereas the lungs lack similar natural targeting mechanisms.Inhalation delivery can reduce systemic exposure, but deposition distribution is influenced by multiple factors—including the delivery device, particle characteristics, the patient’s inspiratory capacity, and disease status—resulting in far greater dose variability than with intravenous administration. Attempting to replicate the experience with the liver in the lungs is a common reason for the repeated setbacks faced by nucleic acid therapeutics in the respiratory field.

 3.1 Local delivery reduces systemic exposure but also introduces new variability

 Inhalation delivery is the natural choice for local pulmonary therapy, but the actual proportion of the inhaled dose that reaches the target cells is influenced by multiple factors.Device type (DPI, pMDI, nebulizer), particle or droplet characteristics (MMAD, FPF), patient inhalation capacity (peak flow rate, inspiratory volume), pulmonary deposition distribution (central vs. peripheral), and disease severity (mucus hyperplasia, airway remodeling, emphysema) collectively determine the effective dose. The actual amount delivered to different patients for the same nominal dose may vary by a factor of several times.

 Table 3.2 Factors Affecting and Methods for Controlling Inhaled Delivery Doses

Factors	Mechanism of Action	Sources of Variability	Control Methods
Device Type	Factors Determining Initial Aerosol Characteristics	DPIs rely on inhalation; pMDIs require coordination	Device-Patient Match
Particle Characteristics (MMAD)	Particles 1–5 μm can be deposited; particles >5 μm strike the pharynx	Batch-to-batch Variability in Formulations	Particle size distribution quality control
Patient inhalation capacity	DPI (Direct Pulverized Inhaler) relies on active inhalation	Age, lung function, acute exacerbations	Inhalation Training and Monitoring
Mucus Barrier	Intercepting nucleic acid carriers	Infection, chronic inflammation exacerbates mucus	Mucolytic pretreatment
Airway Remodeling	Altered Deposition Distribution	Reduced peripheral deposition in critically ill patients	Dose adjusted according to phenotype
Inflammatory environment	Influences cellular uptake and expression	Acute phase vs. stable phase	Timing of administration
Evasion of endosomes	Determines Expression Efficiency	LNP Composition and Cell Type	Formulation Optimization

 Discussing formulation performance, device performance, and patient operation separately is the first step toward understanding the variability in inhalation delivery. Formulation performance is determined by the LNP formulation, particle size, encapsulation efficiency, and stability; device performance is determined by dose release and aerosol characteristics; and patient operation is determined by inhalation coordination, inhalation flow rate, and breath-hold duration. The combination of these three factors determines the actual delivered dose; optimizing any single factor alone is insufficient.Conference reports typically focus only on formulation performance, with insufficient discussion of device performance and patient behavior.

 Action recommendation for this section: When reviewing studies on inhaled nucleic acid drugs or mRNA, first verify whether data on all three categories—formulation performance (particle size, encapsulation efficiency), device performance (FPF, dose release), and patient performance (peak inspiratory flow rate, coordination)—are reported. If any one category is missing, the delivery efficiency data should be considered incomplete and await supplementation.

 From a development strategy perspective, the dose variability of inhaled nucleic acid drugs raises another underestimated issue: the basis for selecting trial doses. If Phase I dose escalation is based solely on nominal doses without considering actual deposition distribution, the recommended Phase II dose may result in inconsistent actual exposure across different patient subgroups.Due to airway remodeling and mucus hyperplasia, peripheral deposition in severely ill patients may be significantly lower than in patients with mild symptoms; thus, the effective exposure from the same nominal dose may be insufficient in severely ill patients. This would directly weaken the evidence of efficacy in severely ill populations.

 The industry currently lacks a unified standard for dose titration of inhaled nucleic acid drugs.Some studies use γ-labeled imaging to assess deposition distribution, but sample sizes are typically limited; other studies report only the nominal dose without providing deposition data. When reviewing studies on inhaled nucleic acid drugs at ERS meetings, asking about “the relationship between the nominal dose and the actual deposited dose” is a fundamental yet critical verification step. If investigators cannot answer this question, the credibility of the dosage recommendation must be discounted.

 3.2 Controllability Must Be Demonstrated for Both Long-Acting Expression and Silencing

 Nucleic acid therapeutics and mRNA aim for sustained expression or silencing, but long-acting properties are not an inherent advantage. If the effect is difficult to modulate, the safety margins must be clearly defined. Documenting the onset time, peak concentration, duration, and decline profile of the effect is a fundamental requirement for evaluating long-acting products. Immunogenicity, cumulative effects from repeated dosing, and protocols for managing adverse events must all be clearly defined.

 Table 3.3 Dimensions for Assessing the Controllability of Long-Acting Nucleic Acid Drugs/mRNA

Long-Acting Dimensions	Questions to Be Addressed	Risk Signals	Management Strategies
Onset of Action	Reaches effective levels within a few days to a few weeks	Slow onset of action delays treatment	Combination with short-acting bridging therapy
Peak Levels	Is the peak expression level within the safety window?	Excessively high peak levels may cause toxicity	Dose titration and monitoring
Duration	Duration of Effect After a Single Dose	Insufficient maintenance requires frequent dosing	Optimizing Dosage Intervals
Elimination Process	How long after discontinuation does the effect wear off?	Adjustments due to excessively slow tapering	Assessment of reversibility
Immune Response	Repeated Administration and ADA Production	Diminished efficacy, hypersensitivity	Immunomonitoring and Drug Switching
Cumulative Effects of Repeated Dosing	Tissue Accumulation and Chronic Toxicity	Uncertainty regarding long-term safety	Maximum cumulative dose
Management of Adverse Events	Interventions in the Event of an AE	High Risk in the Absence of an Antidote	Antagonists or Clearance Strategies

 The key takeaway from the table above is that long-acting products require greater controllability than short-acting products. While short-acting products can be quickly adjusted by discontinuing treatment, once administered, long-acting products may remain active for weeks to months, leaving limited room for managing adverse events during that period. For long-acting products without an antidote, the safety margin must be significantly higher than that of short-acting products; otherwise, clinical acceptability will be compromised.

 Action Recommendations for This Section: When evaluating data for long-acting nucleic acid therapeutics/mRNA, in addition to efficacy metrics, verify at least the following seven aspects: onset of action, peak concentration, duration of action, decline, immune response, accumulation, and adverse event management. Any claim of “long-acting” status that lacks data on the decline of the drug’s effects and a strategy for managing adverse events should be labeled as “to be verified” and should not be incorporated into clinical decision-making.

 4. In vivo gene editing presents the respiratory field not with answers, but with a set of even more challenging questions

 Intellia Therapeutics announced Phase III data for Lonvo-z (NTLA-2002) in the treatment of hereditary angioedema, showing a reduction in attack frequency of approximately 87%. This marks the world’s first in vivo CRISPR therapy to achieve success in a Phase III clinical trial.This signal indicates that in vivo CRISPR is undergoing a higher level of clinical validation; however, HAE is a rare disease of hepatic origin, and there are already established examples—such as Onpattro—for hepatic LNP delivery to serve as references. There is a lack of direct evidence to extrapolate the success of hepatic delivery for HAE to respiratory diseases. Delivery mechanisms, cell types, off-target risks, and long-term monitoring requirements in the respiratory system are entirely different from those in the hepatic system.

 Specific efficacy rates, project names, and regulatory statuses should be verified through company announcements, clinical trial registrations, and regulatory filings prior to formal publication. The 87% figure for Lonvo-z is derived from publicly available Intellia data; the latest figures should be cross-checked on ClinicalTrials.gov and in regulatory filings prior to publication. This article does not directly extrapolate successes in other diseases to respiratory diseases but rather treats in vivo editing as a set of stricter criteria to assess the maturity of respiratory CGT.

 Table 4.1 Differences Between In Vivo Editing Success in HAE and Extrapolation to Respiratory Diseases

Dimension	HAE (Validated by Lonvo-z)	Respiratory Diseases (To Be Verified)	Feasibility of Extrapolation
Target Organ	Liver	Lungs (airways/alveoli/blood vessels)	Low; different delivery mechanisms
Delivery Vehicle	LNP liver targeting (ApoE-mediated)	LNP lung targeting is not yet mature	Requires redevelopment
Target Cells	Hepatocytes	Airway epithelium, alveolar epithelium, immune cells, etc.	Diverse types with varying regenerative capacities
Editing Target	KLKB1 gene (monogenic disease)	Multigenic disorders or monogenic subtypes	High complexity of mechanisms
Clinical Endpoints	Incidence rate (objectively quantifiable)	FEV1, acute exacerbations, PRO	Difficulty in interpreting composite endpoints
Long-term monitoring	Liver function, kidney function	Pulmonary function, imaging, biomarkers	Monitoring System Yet to Be Established
Regulatory Pathway	Accelerated Approval for Rare Diseases	Coexistence of rare and common diseases	Diverse Pathways

 The assessment in the table above is as follows: HAE therapy demonstrates high delivery maturity to the liver, a single target cell type, objective clinical endpoints, and a clear regulatory pathway; respiratory diseases do not meet the same criteria in any of these four areas. Directly extrapolating the success of Lonvo-z to the respiratory field would overlook the actual gaps in delivery, cells, endpoints, and monitoring.

 4.1 Moving from Ex Vivo to In Vivo: Omitting Manufacturing Steps Does Not Equate to Reducing Overall Complexity

 Ex vivo editing, such as CAR-T therapy, requires individualized cell collection, ex vivo transduction, expansion, and reinfusion—a cumbersome and extremely costly process.In vivo editing, which uses carriers such as LNPs to perform gene repair directly within the human body, eliminates the need for individualized manufacturing steps. However, the risks do not disappear; rather, they shift to five areas: delivery, in vivo distribution, off-target effects, immune responses, and long-term monitoring. Equating “eliminating manufacturing steps” with “reducing overall complexity” is a misinterpretation of in vivo editing.

 Table 4.2: Shift in Complexity Between In Vitro and In Vivo Editing

Dimensions of Complexity	Ex vivo Editing	In vivo Editing	Direction of Risk Transfer
Individualized Collection	High (separate for each patient)	Low (universal product)	Simplified in vivo editing
In vitro procedures	High (culture, transduction, quality control)	None	Simplified in vivo editing
Delivery precision	Can be reinfused immediately; precise targeting	Depends on vector-tissue selectivity	In vivo editing becomes more complex
In vivo distribution	Controllable (cell reinfusion)	Distribution across multiple organs requires evaluation	Complexity of in vivo editing
Off-target risk	Can be detected in vitro and then discarded	Irreversible in vivo; prediction required	In vivo editing becomes more complex
Immune response	Reinfused cells may be cleared	Both the vector and the edited product may cause sensitization	Complexities of in vivo editing
Long-term monitoring	Cells can be tracked	Edits are permanent and require lifelong follow-up	Complexity of in vivo editing
Manufacturing Costs	Extremely high (personalized)	Moderate (platform-based, but LNP is expensive)	In vivo editing is simplified but not eliminated

 The table above shows that while in vivo editing simplifies the manufacturing process, it increases complexity in five areas: delivery, distribution, off-target effects, immune response, and monitoring. If any one of these five factors gets out of control, the clinical risks of in vivo editing may exceed those of in vitro editing. Simply describing in vivo editing as “a one-time cure that has already been achieved” obscures these real risks.

 Action Recommendations for This Section: When evaluating in vivo editing projects in the respiratory field, verify the following five aspects separately: delivery precision, in vivo distribution data, off-target detection methods, monitoring of immune responses, and long-term follow-up protocols. Any claim of a “one-time cure” that lacks data on these five aspects should be labeled as “proof of concept” rather than “clinical realization.”

 From a regulatory dialogue perspective, the approval pathway for in vivo editing products differs significantly from that of traditional small molecules and biologics. The FDA and EMA typically require longer follow-up periods for CGT products (15-year long-term follow-up has become a standard requirement for CGT products) and set explicit requirements for the sensitivity of off-target detection methods.For in vivo editing projects in the respiratory field, it is necessary to engage in regulatory discussions regarding three core issues—off-target detection strategies, long-term follow-up protocols, and criteria for discontinuing treatment (e.g., in the event of serious adverse events)—as early as the pre-IND stage. If the project team lacks clear plans for these critical milestones, the regulatory approval timeline will be significantly extended.

 One often-overlooked issue is that the “one-time” nature of in vivo editing leaves very little room for managing adverse events.When CAR-T therapy results in CRS or ICANS, interventions such as tocilizumab or corticosteroids can be used; however, once in vivo editing is complete, the edited products persist permanently within the cells, and there is no antidote to eliminate them. This irreversibility requires safety margins to be set much higher than for reversible therapies. When reviewing in vivo editing respiratory projects during an ERS site visit, probing into the “management strategy in the event of a serious adverse event” is an essential verification step.

 4.2 Cellular Diversity in the Respiratory System Amplifies the Difficulty of Selecting Targets for Editing

 The respiratory system comprises dozens of cell types, including airway basal cells, goblet cells, ciliated cells, Clara cells, type I alveolar epithelial cells, type II alveolar epithelial cells, alveolar macrophages, various T cells, B cells, dendritic cells, fibroblasts, smooth muscle cells, and endothelial cells.Each cell type plays a different role in various respiratory diseases; selecting editing targets requires answering three questions: Which cell types must be targeted for treatment? Can the target cells renew themselves (i.e., can the edit be passed on to daughter cells)? Is there a dose-response relationship between the editing proportion and clinical benefit?

 Table 4.3 Regenerative Capacity and Editing Feasibility of Major Respiratory Cell Types

Cell Type	Renewal Capacity	Role in Respiratory Diseases	Editing Feasibility
Airway Basal Cells	Strong (stem cells)	Source of airway epithelial repair	Editable Genes, Great Potential
Cup cells	In	Mucus secretion; hyperplasia in asthma/COPD	Editing can reduce mucus
Ciliated cells	Terminal differentiation	Ciliary clearance	Not hereditary; requires repetition
Alveolar type II epithelium	Strong (stem cells)	Surfactant secretion, repair	Hereditary (editable)
Alveolar type I epithelium	Terminal differentiation	Gas exchange	Non-heritable
Alveolar macrophages	Self-renewing	Inflammation, clearance	Editing requires targeted delivery
T cells (in the lungs)	Memory cells persist long-term	Immune regulation	Editing can alter immune memory
Fibroblasts	In	Fibrosis	Editing Reduces Collagen Deposition
Endothelial cells	In	Vascular Permeability	Related to pulmonary arterial hypertension

 The key takeaway from the table above is that edits in terminally differentiated cells (cilia cells, type I alveolar epithelium) are not heritable, and the effects of a single edit fade with cell turnover; edits in stem cells (basal cells, type II alveolar epithelium) are heritable, and in theory, a single edit could be effective long-term, but it remains to be demonstrated that the edit frequency is sufficient to sustain clinical benefit.Equating “successful editing” with “clinical benefit” overlooks the critical dose-response relationship.

 In the absence of direct data, the questions “which cell types require editing” and “what editing proportion is sufficient” should be listed as issues to be verified, rather than drawing conclusions on one’s own. This is the minimum requirement of a scientific approach.

 4.3 CMC Must Explain How Each Batch of Product Maintains Consistent Behavior

 Chemistry, Manufacturing, and Control (CMC) is an essential hurdle that in vivo editing products must clear to progress from research to clinical use.The quality of nucleic acid raw materials, the key quality attributes of LNPs (particle size, PDI, encapsulation efficiency, zeta potential), potency assay methods, aseptic production, stability data, and batch-to-batch comparability—each of these requires the establishment of a reproducible testing system. For editing products, it is also necessary to verify whether the testing methods can correlate delivery efficiency, editing efficiency, and potential risks (off-target effects, chromosomal rearrangements).

 Table 4.4 Key CMC Quality Attributes for In Vivo Editing Products

CMC Dimension	Key Quality Attributes	Test Method	Common Issues
Nucleic Acid Raw Materials	Purity, Sequence Integrity, Concentration	HPLC, Mass Spectrometry, UV	Condensation, Degradation
LNP Particle Size	Target range: 60–120 nm	DLS, NTA	Batch-to-batch drift
PDI	<0.2 indicates uniformity	DLS	A broad distribution indicates heterogeneity
Encapsulation Efficiency	>80% is the target	RiboGreen method	Free nucleic acids affect safety
Zeta potential	Close to neutral or slightly negative	Electrophoretic light scattering	Positive potential increases immunogenicity
Efficacy testing	In vitro editing efficiency	Cell line editing assay	Uncertain Correlation Between In Vitro and In Vivo Results
Sterile production	Sterility and Endotoxins	Sterile Cultivation, LAL	High Difficulty in Achieving Sterility During LNP Production
Stability	Storage at -20°C or 2–8°C	Accelerated stability testing	Freeze-thaw cycles affect particle size
Batch-to-batch comparability	Consistency of Key Properties	Statistical comparison across multiple batches	Property Drift After Scale-Up
Off-target detection	Genome-wide off-target sites	GUIDE-seq, CIRCLE-seq	In vitro testing may not reflect in vivo results

 The key takeaway from the table above is that CMC is not merely paperwork; it is the reproducible assurance of a product’s performance. Failure to demonstrate batch-to-batch comparability implies that different patients receiving the “same product” may experience significant variations in particle size, encapsulation efficiency, and potency, which would severely compromise the interpretability of clinical results. Treating CMC as a regulatory burden rather than a scientific issue is a common cognitive bias in the CGT field.

 Action Recommendations for This Section: When evaluating in vivo editing programs, in addition to clinical data, verify six key CMC data points: LNP particle size, PDI, encapsulation efficiency, potency testing, batch-to-batch comparability, and off-target activity testing. Any claim of “platform-based manufacturing” lacking batch-to-batch comparability data should be labeled as “to be validated.” A platform narrative is only valuable if it is supported by batch consistency and clinical comparability.

 5. Small Molecules and Immunotherapy May Still Be the More Adjustable, Realistic Solutions

 Maintaining a balanced perspective beyond the hype surrounding one-time therapies is the fundamental stance of this article. Small molecules—with their adjustable exposure, reversible effects upon discontinuation, and mature manufacturing processes—may be better suited for chronic respiratory diseases requiring ongoing management; immunotherapy requires a delicate balance between inflammation control and infection risk and offers clear value for patients with specific pathways. Equating “technological advancement” with “clinical priority” risks overlooking solutions that truly address patients’ current needs.

 Table 5.1 Adjustability and Indication Matching Across Different Technology Categories

Technology Category	Modulability	Reversibility	Manufacturing Maturity	Suitable Disease Types
Small molecules (oral)	High (controllable exposure)	High (clearance upon discontinuation)	Mature	Chronic diseases requiring ongoing management
Small molecules (inhaled)	High	High	Mature	Localized airway diseases
Immunotherapy	Moderate (dose adjustment)	Moderate (half-life of several weeks)	Relatively mature	For cases with well-defined inflammatory pathways
Biologics	Medium to low (fixed dosing interval)	Medium (long half-life)	Mature	Type 2 inflammation, specific phenotypes
Nucleic acid drugs/mRNA	Low (long-acting)	Low (sustained action)	Under development	Rare diseases, monogenic
In vivo editing	Extremely low (one-time)	Extremely low (irreversible)	Early	Monogenic diseases, rare diseases

 The table above shows that the order of modifiability from highest to lowest is: small molecules > immunotherapy > biologics > nucleic acid therapeutics/mRNA > in vivo editing. The order of reversibility is largely consistent. Chronic respiratory diseases require long-term management, and modifiability and reversibility are important factors in clinical decision-making. Placing irreversible, one-time editing as the first-line treatment for chronic diseases is inconsistent with the logic of disease management.

 5.1 The convenience of oral or inhaled administration must be weighed against long-term safety

 The convenience of small molecules (oral, inhaled, home use) constitutes a differentiating factor only when efficacy is stable and risks are manageable. Assessing drug interactions, organ toxicity, signs of infection, adherence, and real-world usage conditions are necessary steps in evaluating the long-term value of small molecules. Convenience alone does not constitute a clinical advantage.

 Table 5.2 Dimensions for Assessing the Long-Term Safety of Small Molecules

Safety Dimensions	Assessment Indicators	Clinical Issues	Management Strategies
Drug Interactions	CYP450 Enzyme Inhibition/Induction	Changes in Exposure with Concomitant Medications	Dose Adjustment, Avoid Concomitant Use
Hepatotoxicity	ALT, AST, Bilirubin	Risk of DILI	Regular Monitoring, Thresholds for Discontinuation
Nephrotoxicity	Creatinine, eGFR, Urinary Protein	AKI or chronic kidney damage	Dose adjustment based on renal function
Cardiovascular	QT interval, blood pressure, heart rate	Risk of life-threatening arrhythmias	Baseline ECG, monitoring in high-risk patients
Signs of infection	Incidence and severity of infection	Immunosuppression-Related Infections	Prevention, early detection
Adherence	Prescription fill rates, electronic monitoring	Real-world Efficacy Decline	Simplified regimens, patient education
Real-world use	Electronic health records, registry data	Differences from the trial population	Postmarketing Studies

 The table above shows that the long-term safety assessment of small molecules involves at least seven dimensions, each of which requires active monitoring. Safety signals observed in clinical trial populations may be amplified in real-world settings due to comorbidities, concomitant medications, and differences in adherence. Directly extrapolating short-term trial data to long-term use may underestimate the actual risk.

 Action Recommendations for This Section: When evaluating long-term usage data for small molecules, verify at least the following seven areas: drug interactions, hepatotoxicity, nephrotoxicity, cardiovascular events, infections, adherence, and real-world data. If data for any of these areas is missing, mark it as “to be supplemented” and do not include it in the long-term usage recommendations.

 5.2 Combination regimens must specify the purpose of each component

 Combination therapy is common in respiratory diseases, but the rationale for the combination must be clearly defined. Distinguish whether the combination is intended to target different inflammatory pathways, improve acute exacerbations, or address structural changes (such as airway remodeling or emphysema). Document the contribution of each component and any incremental toxicity, and avoid substituting complementary mechanisms for clinical validation.

 Table 5.3 Objectives and Validation Requirements for Combination Therapy Regimens

Purpose of Combination Therapy	Typical Combinations	Validation Requirements	Common Misconceptions
Coverage of Different Inflammatory Pathways	Anti-IL-5 + Anti-IL-4Rα	Independent Contributions of Each Component	Assuming that complementary mechanisms are effective
Improvement in Acute Exacerbations	ICS + LABA + LAMA	Comparison of Acute Exacerbation Rates	Additive rather than synergistic effects
Management of Structural Disease	Anti-inflammatory + antifibrotic	Imaging and Pulmonary Function	Confusion Between Inflammation and Structural Changes
Reducing corticosteroid dependence	Biologics + Tapering of Oral Corticosteroids	Safe Corticosteroid Tapering	Relapse due to too rapid tapering
Overcoming Resistance	Change or Add Medication	Testing for Mechanisms of Resistance	Empirical addition of medication
Reducing dose-related toxicity	Low-dose combination vs. high-dose monotherapy	Non-inferiority design	Combination Therapy Increases Costs Without Reducing Toxicity

 The key takeaway from the table above is that combination therapy must have a clear objective, and each component must demonstrate an independent contribution or synergistic effect. Using “complementary mechanisms of action” as a sufficient justification for combination therapy—and bypassing clinical validation—will subject patients to unnecessary dosing and costs. Complementary mechanisms of action are a hypothesis; clinical benefit is the conclusion.

 Action Recommendations for This Section: When evaluating combination regimens, first ask about the purpose of the combination (pathway coverage, acute exacerbations, structural changes, corticosteroid tapering, resistance, dose-related toxicity), then verify the data on the independent contributions of each component and any incremental toxicity. If complementary mechanisms are not supported by clinical data, label them as “to be validated.”

 6. Clinical, R&D, and industry teams should ask different questions based on the same results

 A single clinical result holds different significance for different teams. Clinical teams assess whether it can alter patient pathways; translational teams evaluate the validity of biomarkers and delivery methods; and industry teams determine the feasibility of CMC, cost, and regulatory follow-up. Ensuring that a paper serves at least these three types of readers is a prerequisite for translating conference data into decision-making. For the same set of data, the “questions” identified by these three types of readers are entirely different.

 Table 6.1: Different Questions Raised by the Three Teams Regarding the Same Result

Team	Core Question	Basis for Judgment	Decision Output
Clinical Team	Can the patient pathway be modified?	Acute Exacerbation, Hospitalization, PRO, Safety	Inclusion in care pathways, prescription adjustments
Translation Team	Are Biomarkers and Delivery Mechanisms Valid?	Samples, Assays, Target Cells, Efficacy Markers	Mechanism validation, next study design
Industry Team	CMC, costs, and regulatory feasibility	Batch-to-batch consistency, cost structure, follow-up requirements	Investment, Collaboration, Regulatory Communication

The table above shows that the three types of teams focus on completely different aspects of the same research data. Clinical teams focus on “how this benefits patients,” translational teams focus on “whether the mechanism holds up,” and industry teams focus on “whether it can be developed and sold.” Lumping these three types of questions together will cause the interpretation of meeting data to deviate from decision-making needs.

 6.1 Clinical Teams Focus First on Acute Exacerbations and Patient-Reported Outcomes

 Changes in lung function (FEV1) are objective measures, but clinical decision-making requires consideration of acute exacerbations, hospitalizations, corticosteroid use, symptoms, and quality of life. These indicators reflect patients’ day-to-day status and serve as the direct basis for adjusting clinical pathways. The length of the follow-up period determines the reliability of conclusions regarding efficacy and safety.

 Table 6.2 Core Indicators of Interest to Clinical Teams and Follow-up Requirements

Clinical Indicators	Clinical Value	Follow-up Requirements	Common Data Gaps
FEV1 Improvement	Relief of Airflow Limitation	At least 12 weeks	Long-term maintenance data
Reduction in Acute Exacerbations	Disease stability	At least 12 months	Breakdown of severe acute exacerbations
Reduced hospitalizations	Use of healthcare resources	At least 12 months	Distinction between emergency visits and hospitalizations
Reduced use of corticosteroids	Reduced side effects	At least 6 months	Safe tapering of oral corticosteroids
Improvement in Symptoms (ACT/ACQ)	Daily well-being	At least 12 weeks	Has the MCID been met?
Quality of Life (SGRQ)	Overall Health Perception	At least 12 weeks	Was the MCID met?
Long-term safety	Rare adverse events	At least 2 years	Long-term registry data

 The table above shows that the metrics required for clinical decision-making go far beyond FEV1 alone. Acute exacerbations, hospitalizations, corticosteroid use, symptoms, and quality of life—these five factors constitute the core of “patient-perceived benefit.” If a study reports only improvements in FEV1 but lacks data on these five factors, the basis for clinical decision-making is incomplete. Studies with a follow-up period of less than 12 months have limited credibility regarding conclusions on acute exacerbations.

 Action recommendation for this section: When reviewing study data, first confirm whether the primary endpoints include acute exacerbations or patient-reported outcomes (PROs), then verify that the follow-up period is sufficient. Studies showing a significant improvement in FEV1 alone but lacking data on other indicators should be classified as mechanism studies rather than evidence for clinical decision-making.

 6.2 Translational Teams Should First Assess Whether the Sample Supports the Mechanism

 The core task of the translational team is to determine whether the biomarker and delivery strategy are valid. The timing of tissue or body fluid sample collection, target cell types, effectrator markers, and analysis of non-responders—each of these must be clearly defined. Distinguish between correlation and causal evidence, and avoid overinterpreting mechanisms based on a small number of responders.

 Table 6.3 Sample and Mechanism Issues of Concern to the Translational Team

Translational Issues	Sample Type	Time Point of Testing	Common Misinterpretations
Signal Pathway Activation	Blood, sputum, BAL	Baseline, post-treatment	Mistaking blood markers for intrapulmonary markers
Target cell arrival	Bronchial biopsy, BAL cells	Early post-administration	Treating distribution as uptake
Editing efficiency	Biopsy tissue	Several weeks after administration	Treating DNA editing as a functional change
Efficacy markers	Proteins, mRNA, functional assays	Peak and steady-state	Interpreting changes in markers as clinical benefit
Cases of Treatment Failure	Full-cohort analysis	Time of Treatment Failure	Analysis of Responders Only
Off-target detection	Whole-genome	Post-dosing	In vitro testing Extrapolation to in vivo
Immune response	ADA, cellular immunity	After repeated dosing	Interpreting short-term absence of ADA as long-term safety

 The table above shows that translational research teams have far higher requirements for samples than clinical teams. While clinical teams may accept the conclusion that “treatment is effective,” translational teams must answer “why it is effective, for whom it is effective, and why it fails in some individuals.” Interpreting changes in correlative biomarkers directly as causal mechanisms is a common error in translational research. Mechanism analysis in a small number of responders requires particular caution; over-generalization can mislead the design of subsequent studies.

 Action Recommendation for This Section: When reviewing translational research, first confirm the sample collection time points and target cell types, then verify the analysis of efficacy biomarkers and cases of treatment failure. Any mechanistic conclusion based solely on data from responders should be labeled as “pending independent validation.”

 6.3 CMC and BD Teams Should First Assess Whether the Platform Can Be Reused Across Projects

 The core question for industry teams is: How much of the delivery, analytical methods, efficacy testing, and manufacturing processes can be reused, and which elements must be rebuilt specifically for the indication? A platform narrative is only valuable if it holds up in terms of batch consistency and clinical comparability. Packaging the success of a single project as a platform is a common form of over-marketing in the CGT field.

 Table 6.4 Elements That Can Be Reused vs. Those That Must Be Rebuilt Across Projects

Platform Dimension	Reusable Elements	Elements Requiring Reconstruction	Validation Requirements
LNP Delivery	Lipid Composition, Preparation Process	Tissue-selective formulations	Multi-tissue delivery data
Analytical Methods	Particle Size and Encapsulation Efficiency Assays	Efficacy Testing (Cell Type-Dependent)	Method Validation Cross-Project
Efficacy Testing	General Editing Assay	Target Cell-Specific Functional Assays	In vivo–in vitro correlation
Manufacturing Process	LNP Production and Filling	Product-Specific Quality Control	Scalability and Comparability
Clinical Design	Dosage Strategy Framework	Endpoints and Population	Cross-Indications Comparability
Regulatory Communication	CMC Framework	Product-Specific Issues	Pre-IND Meetings
Cost Structure	Fixed Costs (Facilities)	Variable Costs (Raw Materials)	Cost Curve After Scaling Up

 The table above shows that the platform narrative must distinguish between two categories of elements: “reusable” and “requiring reconstruction.”LNP lipid composition and preparation processes can be reused, but tissue-selective formulations must be rebuilt for each indication; general particle size testing can be reused, but potency testing depends on the target cell type; the manufacturing process framework can be reused, but product-specific quality control must be rebuilt. Packaging all elements as a “validated platform” obscures the true costs and risks associated with rebuilding.

 Action Recommendation for This Section: When evaluating a CGT platform narrative, systematically review the seven components—LNP delivery, analytical methods, efficacy testing, manufacturing processes, clinical design, regulatory communications, and cost structure—item by item to distinguish between reusable and reconstruction-required elements. Any claim of a “validated platform” lacking cross-project clinical comparability data should be labeled as “proof of concept.”

 7. ERS On-Site Inspection Checklists for bio europe 2026 Participants Should Begin with Patient-Centered Questions

 Whether at ERS or the Barcelona biotech summit, conference sessions are information-dense; simply reviewing them according to a “list of new technologies” can lead to superficial judgments. A checklist that begins with patient-centered questions helps attendees contextualize each study within the framework of clinical decision-making. It is recommended to document the following eight items: disease and patient subtypes, treatment goals, target cells, administration routes, durability of efficacy, safety and reversibility, manufacturing and testing, and next steps for evidence. After the conference, categorize and update these entries into three groups: “may change practice,” “worth following,” and “insufficient evidence.”

 Table 7.1: Eight Dimensions of the ERS On-Site Checklist

Checklist Dimensions	Core Question	Assessment Criteria	Post-Conference Categorization
Disease and Patient Subtyping	Which phenotype/genotype is the study targeting?	Predefined Subgroups + Sample Size	Changes in Practice/Follow-up/Limitations
Treatment Goals	Modifying the pathway or managing symptoms	Alignment with patient needs	Practice changes/follow-up/shortcomings
Target Cells	Editing/Which Cell Types Are Targeted by the Drug	Target cell data	Changes in Practice/Monitoring/Shortcomings
Route of Administration	Inhalation, systemic, in vivo	Delivery Feasibility	Changes in Practice/Monitoring/Limitations
Duration of Effect	Single-dose/Repeated-dose/Long-term maintenance	Follow-up Period	Changes in Practice/Follow-up/Limitations
Safety and Reversibility	Reversible, monitorable, antidote	Safety Boundaries	Changes in Practice/Monitoring/Shortcomings
Manufacturing and Testing	CMC Batch-to-Batch Consistency	Comparability data	Changes in Practice/Tracking/Shortcomings
Next Steps for Evidence	What Additional Studies Are Needed	Clear Study Design	Practice Change/Follow-up/Limitations

 The eight dimensions in the table above constitute a checklist for “Starting with the Patient’s Problem.” Each piece of data from every study can be plotted onto this table for evaluation. “Change in Practice” requires all eight dimensions or the core items to be sufficiently met; “Follow-up” indicates that some dimensions need to be supplemented; “Insufficient Evidence” means that key dimensions are missing or the methodology is unreliable. By reviewing each presentation against this table, the notes taken after the conference will be of real value for making informed judgments.

 7.1 Verify the Official Program and Source Materials Before the Meeting

 Dates, locations, online participation methods, and topics are subject to the ERS official website; project data is subject to abstracts, papers, trial registrations, and regulatory documents. Information regarding project progress in 2026 should be treated only as a topic suggestion and should not be presented as confirmed fact until verified. Pre-conference preparation determines the quality of on-site judgment.

 Table 7.2 Authoritative Sources for Verifying Conference Information

Information Type	Authoritative Sources	Verification Points	Common Errors
Basic Conference Information	ERS Official Website: ersnet.org	Date, Location, Online Format	Reliance on Secondhand Accounts
Agenda Items	ERS Official Program	Time, Speaker, Topic	Based on memory
Research data	Original Abstract	Sample Size, Endpoint, Follow-up	Relying solely on press releases
Trial registration	ClinicalTrials.gov	Enrollment, Status, Primary Endpoint	Based on company press releases
Regulatory Status	EMA and FDA Documents	Approval, Conditional Approval, Labeling	Treating an application as an approval
Company Announcements	Official Website, SEC Filings	Data Details, Timeline	Focusing Only on News Headlines
Peer Review	Journal Articles	Quality of Peer Review	Treating Preprints as Definitive

 The table above shows that there are authoritative sources for each type of information. For basic conference information, refer to the ERS official website; for research data, refer to the original abstract; for trial registrations, refer to ClinicalTrials.gov; for regulatory status, refer to EMA and FDA documents; for company announcements, refer to official websites and regulatory filings; and for peer-reviewed articles, refer to the journal. Treat these sources as the “factual baseline,” and treat press releases, secondhand accounts, and social media as leads rather than conclusions.

 Action Recommendations for This Section: Complete at least three verifications before the conference—confirm basic information and the agenda on the ERS official website; verify the status and endpoints of key trials on ClinicalTrials.gov; and confirm product approval status in regulatory documents. If any data conflicts across different sources, rely on the authoritative source.

 7.2 Do not use a single conference abstract to announce a “one-time cure” after the meeting

 Conference abstracts are preliminary reports; sample size, control design, follow-up duration, off-target detection, long-term monitoring, and reproducibility may all be incomplete. Early signals should be described using cautious phrasing such as “shows potential” or “forms a validating signal,” rather than absolute terms like “cure,” “breakthrough,” or “milestone.” Elevating a single abstract to the status of a definitive conclusion is the most common form of overinterpretation in conference communications.

 Table 7.3 Limitations of Conference Abstracts and Validation Pathways

Limitations of Abstracts	Items Requiring Confirmation	Follow-up Validation Pathways	Risk of Overinterpretation
Sample Size	Is it sufficient to support the conclusions?	Larger-Sample Studies	False-positive results in small samples
Control Design	Randomized, blinded, controlled	Confirmatory Phase III	Open-label studies overestimate efficacy
Follow-up Duration	Short-term vs. Long-term	Extended follow-up	Extrapolation of short-term data to long-term outcomes
Off-target detection	Method Sensitivity	Whole-genome testing	Negative results do not necessarily indicate the absence of off-target effects
Long-term monitoring	Cumulative Adverse Events	Registration System	Rare AEs Not Identified
Reproducibility	Independent Cohort Validation	Multicenter study	Single-center results are difficult to replicate
Endpoint Selection	Primary vs. Secondary	Confirmatory Endpoints	Secondary Endpoints Treated as Primary
Subgroup Analysis	Pre-specified vs. Post-hoc	Pre-specified Phase III Subgroup	Post-hoc analysis as a conclusion

 The table above shows that a single abstract has at least eight limitations that need to be validated in confirmatory studies. Recording all eight of these limitations in your conference notes is a fundamental practice for avoiding overinterpretation. Restrained phrasing such as “shows potential” and “provides a signal for validation” is not conservatism—it is science.

 Action Recommendation for This Section: When organizing your meeting notes afterward, check each study against the eight items in the table above and mark them as “Verified” or “To Be Verified.” Any statements such as “one-time cure” or “breakthrough,” if lacking at least one independent confirmatory study, should be rewritten as “provides a signal for further validation” or “shows potential.”

 Another risk in conference communication is the chain of amplification through “abstracts → press releases → social media.” After data from the original abstract is packaged in press releases and retold on social media, conclusions are often simplified into more attention-grabbing statements. Clinicians and R&D personnel need to return to the original abstracts for verification to avoid being misled by overinterpretation in the communication chain. At the ERS conference, listening directly to presentations and reading the abstract wall is more effective for maintaining the accuracy of one’s judgment than relying on secondhand accounts.

 8. Conclusion: The dividing line in precision respiratory therapy lies in the ability to deliver advanced mechanisms to the right location

 Full Summary: Biologics, nucleic acid therapeutics, small molecules, and in vivo editing will not simply replace one another based on the novelty of their technologies. Only approaches that can identify the right patients, reach the right cells, maintain controlled effects, and establish manufacturable pathways can truly improve long-term respiratory care. These four factors constitute the defining criteria for precision respiratory therapy discussed at the ERS International Congress.

 Table 8.1: The Four Defining Criteria for Precision Respiratory Therapy

Criterion Dimension	Failure Criteria	Criteria Met	Criteria
Identifying the Correct Patients	Post-hoc subgroups, single threshold	Predefined subgroups, multifactorial matrix	Protocol-defined + independent validation
Reaching the Correct Cells	Missing delivery data	Distribution + Uptake + Functional Data	Imaging + Biopsy + Biomarkers
Maintain Controlled Effect	No elimination data, no antidote	Onset + Peak + Duration + Offset + Management	Complete pharmacokinetic profile
Establish a manufacturable pathway	Lack of batch-to-batch comparability	Stability of key CMC attributes	Statistical Comparison Across Multiple Batches

 The four thresholds listed in the table above represent the minimum requirements for determining whether any precision treatment regimen for respiratory diseases can advance to real-world clinical practice. Failure to meet any one of these criteria means the regimen remains in the research phase and does not enter clinical decision-making. Using these thresholds as an evaluation framework helps avoid being distracted by the novelty of technology, theoretical mechanisms, or single-study data, and instead refocuses attention on what patients truly need.

 The positive Phase III results for in vivo gene editing in HAE are a signal indicating that CGT is undergoing a higher level of validation. However, the four key aspects of respiratory diseases—delivery, cells, endpoints, and monitoring—are entirely different from those of HAE; there is no basis for directly extrapolating HAE’s success to respiratory diseases. The true progress of precision therapy for respiratory diseases requires evaluation item by item against these four thresholds, rather than being judged based on a single signal from a particular technology.

 What is worth noting at ERS 2026 is not the number of new technologies, but whether these technologies—through collaboration among patients, clinicians, and researchers—can address the four key challenges: identification, delivery, controllability, and manufacturing. Approaches that address these four challenges, regardless of the technology’s novelty, are worth tracking; those that do not, no matter how appealing the concept, should be approached with caution. This is the most important insight to bring back to clinical and R&D decision-making after the conference.

 From an industry investment perspective, the evaluation framework for precision respiratory therapy should also return to these four criteria. Directly translating the hype surrounding CGT into investment priorities for the respiratory sector risks overlooking the actual gaps in delivery, cells, endpoints, and monitoring. The positive Phase III results for HAE are cause for celebration, but they represent a success in hepatic delivery, not in respiratory delivery.Investments in respiratory CGT require separate evaluation of four key areas: delivery platforms, target cell coverage, clinical endpoint design, and long-term monitoring systems—and the maturity of each must be independently verified.

 From the patient’s perspective, the defining line for precision therapy in respiratory medicine ultimately lies in “whether an advanced mechanism can be delivered to the correct location.” This statement may sound simple, but it encompasses four layers of meaning: patient identification, cellular targeting, maintaining control, and establishing a manufacturing pathway. If any one of these is missing, the advanced mechanism will remain confined to the laboratory. If attendees at ERS 2026 can reflect on these four layers after each presentation, the analytical value of their conference notes will be significantly higher than if they merely collect information based on a technical checklist.

 9. ERS 2026 Frequently Asked Questions for bio europe 2026 Attendees

 9.1 When and Where Will the ERS International Congress 2026 Be Held?

 The ERS International Congress 2026 will take place from September 5 to 9, 2026, in Barcelona, Spain. Both in-person and virtual participation options have been officially confirmed; please check the ERS website for the latest arrangements prior to the event. The conference typically attracts approximately 20,000 delegates and is one of the world’s largest gatherings in the fields of respiratory science and clinical practice.

 9.2 What Innovative Treatment Areas Should Be Watched at ERS 2026?

 Based on the core topics outlined in the conference agenda, the following areas are worth watching at ERS 2026:

 **Biologics and Monoclonal Antibodies**: Focus on subgroup analysis and long-term management data for pathways such as Type 2 inflammation, IgE, IL-5, and IL-4Rα.

 **Nucleic acid therapeutics and mRNA**: Focus on delivery technologies (inhaled LNP, tissue selectivity) and data on the controllability of long-acting expression or silencing.

 **Small Molecules**: Focus on long-term safety, resistance management, and real-world adherence for new oral and inhaled targets.

 **Immunotherapy**: Focus on data balancing inflammation control and infection risk.

 **In vivo gene editing**: Monitored as a related trend; current positive Phase III signals come from non-respiratory diseases such as HAE, while respiratory indications remain in the early stages. Do not mistakenly list this as a confirmed main agenda item.

 9.3 Why Delivery Is Key for Respiratory Nucleic Acid Drugs

 Delivery is critical for respiratory nucleic acid therapeutics for three main reasons:

 **Complexity of the Pulmonary Barrier**: Mucus layers, ciliary clearance, macrophage phagocytosis, and surfactants collectively form a delivery barrier, which is entirely different from the permeability mechanisms of hepatic sinusoids.

 **Diversity of Target Cells**: Dozens of cell types—including airway epithelium, alveolar epithelium, immune cells, and fibroblasts—play different roles in various diseases, making it difficult to target specific cell types.

 **Dosage Influenced by Delivery Devices**: Inhalation devices, particle characteristics, patient inspiratory capacity, and pulmonary deposition distribution collectively determine the actual delivered dose; the effective dose for the same nominal dose may vary by a factor of several times among different patients.

 One cannot simply extrapolate pulmonary effects based on hepatic delivery experience; this is the fundamental reason why respiratory nucleic acid drug development requires independent solutions to delivery challenges.