U-BIOPRED (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes) → a 5-year European project to understand more about severe asthma Update: start of project year 4

Pre-Clinical studies are not predictive Target compounds = 5000 – 6000 Pre-Clinial Studies = 250 Phase I = 5 Approved Drug = 1

Why? Lack of validated biomarkers Underperforming preclinical models Inadequate and incomplete sub-phenotyping Insufficient understanding of disease mechanisms.

Hypothesis The use of biomarker profiles comprised of various types of high-dimensional data, integrated with an innovative systems biology approach into distinct phenotype handprints, will enable significantly better prediction of therapeutic efficacy than single or even clustered biomarkers of one data type, and will identify novel targets.

Despite many challenges UBIOPRED is producing.

What UBIOPRED is producing: Large cohort & biobank of deeply phenotyped adult and paediatric patients ‘Handprints’: stratification of severe asthma Preclinical models more reflective of clinical disease A GMP viral challenge exacerbation model

Cohorts

Adult Cohort Total planned Actual total Severe Asthma Severe Asthma + smoking Hx Mild Asthma No lung disease TOTAL

Paediatric Cohort Total planned Actual total School aged severe asthma School aged mild asthma5056 Pre-school severe wheeze7354 Pre-school mild/mod wheeze6046 TOTAL298258

Cohorts year 3 Achievements Recruitment accelerated Interim analysis conducted Challenges Data cleaning –More resource to be applied More mild asthma bronchs needed –Recall subjects for bronchs # of exacerbation visits –More focus

Cohorts year 4 focus Finishing recruitment More mild asthma bronchs Data cleaning Increase exacerbation visits Publications

Multiple data types are integrated into a ‘handprint’ to identify sub-phentoypes.

Topographical clustering on sputum and lung function produces clear clusters.

‘Handprints’ year 3 Achievements Analysis workflows established and tested transMART knowledge management platform in use –Now supported by eTRIKS Interim analysis shows clustering with lipidomics Preliminary ‘Handprints’ (clusters) Challenges Waiting for samples and clean data –Interim analyses done on what is available Coordinating analysis efforts –Meetings every 2 months

‘Handprints’ – focus year 4 Ongoing interim analyses Question/publication based iterative analyses – workflows working at full speed Interactions with other EU/IMI projects Publications

Laboratory Models

Step 1: establish “asthmatic phenotype” AHR induction by passive sensitization ? Pre-incubation with serum of non-allergic donor Pre-incubation with serum of allergic donor Images before allergen exposure Images after allergen exposure Precision lungs are a promising model

Laboratory models year 3 Achievements Determined that chronic House Dust Mite mouse model cannot be exacerbated by virus Establihsed CFA/HDM model in two company and one academic institution –Has mixed Th1/Th2/Th17 phenotype and can be exacerbated. Explant model established Promising work on precision cut lung slices Challenges Getting viral exacerbations –Switch to influenza from rhinovirus Linking with clinical data –Lipidomics to be done in light of interim analysis results

Laboratory models focus year 4 5 publications early 2013 Transcriptomics and analyte panels on samples Getting data into transMART Establish CFA/HDM in other labs Development of precision cut lung models

Human Viral challenge model year 3 Achievements GMP virus produced Protocol for viral challenge study developed Study team organized Challenges Viral production low titre –Rerun at subcontractors cost – now with good titre Virus with reverse transcriptase activity –Proven non-infective and is a known artifact Withdrawal of Pfizer –Roche temporarly then left –Now with Merck and Merck study team

Human Viral Challenge models focus year 4 Viral challenge study Analysis plan and linkage with ‘Handprint’ teams Storage of virus

UBIOPRED Collaboration Successes Two new partners Exactly the same animal model established in 3 different laboratories Linkage with eTRIKS – IMI’s translational research knowledge management project Every working group contains crucial members from both EFPIA and Academic partners Challenges Withdrawal of Pfizer Re-organization to enable focus on analysis Shifting resource committments Delays in contracting & direct financial distribution

Involvement of patients Online forum for patients initiated Patient representative engagement in working teleconferences Patient representatives at yearly meeting