Harrogate, 30Mar09

ANTI-TUBERCULOSIS DRUG R&DPECULIARITIES, PIPELINE &

INITIATIVES

P. Olliaro WHO/TDR, Geneva, CH & University of Oxford, UK

Bellagio, July 2014

Harrogate, 30Mar09

Generic R&D ProcessTarget identification:

Discovery: Lead identification(hit to lead)

Translation (druggability, non-clinical pharmacology) Development candidate, IND

Development (Clinical Ph 1-3 + CMC + Non-clinical) Registration

Access, Post-marketing studies/surveillance, Intervention & Implementation/Operational research

Harrogate, 30Mar09

WHAT'S SPECIAL ABOUT TB DRUG R&D

Treating TB means dealing (simultaneously and sequentially) with bacilli in different metabolic status and in different environmentsWhich requires a combination of compounds with different but integrated PK/PDsNeed new COMBINATIONS, not individual drugs

Harrogate, 30Mar09

Target identification:Discovery: Lead identification(hit to lead)

Translation (druggability, non-clinical pharmacology) Development candidate, IND

Development (Clinical Ph 1-3 + CMC + Non-clinical) Registration

Access, Post-marketing studies/surveillance, Intervention & Implementation/Operational research

Harrogate, 30Mar09

WHO DOES IT – PHARMA-DRIVEN:1. Novartis Institute for Tropical Diseases (NITD)

http://www.nibr.com/research/developing_world/NITD/2. GSK Tres Cantos Open Lab Foundation http://

www.gsk.com/research/research-funding/tres-cantos-open-lab-foundation.html

3. Lilly TB Discovery Initiative (TBDDI) (not-for-profit PDP) https://openinnovation.lilly.com/dd/about-open-innovation/tb-drug-discovery-initiative.html

4. TB Drug Accelerator (TBDA) http://www.bioendeavor.net/BDDirectory_2658.asp?itemId=10873

http://www.astrazeneca.com/Research/news/Article/25062012--seven-pharmaceutical-companies-join-academic-researchhttp://drugdiscovery.pharmaceutical-business-review.com/news/eisai-joins-tuberculosis-drug-accelerator-partnership-to-discover-new-tuberculosis-treatments-251113

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WHO DOES IT – OTHERS:1. Tuberculosis drug discovery TBD-UK

http://www.tbd-uk.org.uk/2. Institute for TB Research (ITR) at UIC

http://www.tuberculosisdrugresearch.org/3. Genome databases at the Broad Institute

http://www.broadinstitute.org/annotation/genome/mtb_drug_resistance.1/DirectedSequencingHome.html

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ISSUES:1. For overview see e.g. Koul et al, Nature 2011 - http://

www.nature.com/nature/journal/v469/n7331/full/nature09657.html

2. General antibiotic resistance: a problem for some classes of anti-tuberculosis drugs (aminoglycosides, fluoroquinolones, etc.) in general use

3. Pharma overall disinvesting from infectious diseases and antibiotics

4. Limited innovation (novel chemical classes); little chance of ‘piggy-backing’ from anti-infective R&D

5. 'Pool' of compounds + sources (private, public)

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Target identification:Discovery: Lead identification(hit to lead)

Translation (druggability, non-clinical pharmacology) Development candidate, IND

Development (Clinical Ph 1-3 + CMC + Non-clinical) Registration

Access, Post-marketing studies/surveillance, Intervention & Implementation/Operational research

Harrogate, 30Mar09

WHO DOES IT:1. Individual companies/sponsors2. PreDiCT-TB - public-private partnership

www.predict-tb.euFunded by the EU Innovative Medicines Initiative, [3 pharma (GSK, Sanofi, Janssen) + 2 biotech (ZF Screens, Microsens Medtech) + 15 academic partners (headed by the University of Liverpool)]Multidisciplinary consortium "to create a new integrated framework for TB drug development, making optimal use of preclinical information to design the most efficient clinical trials"

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ISSUES:1. No mechanisms to move candidates to 'developers'

(apart from GATB?)2. Drug action depends on metabolic status of MTB.

Need multiple models + way to integrate them for log-phase, mid-phase & dormant MTB

3. How to test combinations as opposed to individual compounds

4. Predictivity of animal models? 5. How to account for immune response?

Harrogate, 30Mar09

Target identification:Discovery: Lead identification(hit to lead)

Translation (druggability, non-clinical pharmacology) Development candidate, IND

Development (Clinical Ph 1-3 + CMC + Non-clinical) Registration

Access, Post-marketing studies/surveillance, Intervention & Implementation/Operational research

Harrogate, 30Mar09

WHO DOES IT – THE PIPELINE:1. http://www.newtbdrugs.org/pipeline.php (last

update 2013 = out-of-date)2. Individual companies; GATB main actor; how many

companies still involved? 3. Limited spectrum of chemicals4. No drug in Phase I5. No headway in treatment shortening: gatifloxacin 4-

month regimen not non-inferior to 6-month standard regimen (exc'pt non-cavitary disease ?)

6. Newly-diagnosed vs. multidrug resistant TB (a false dichotomy?)

7. REGULATORY AGENCY role – requirements need to be adapted to TB

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WHO DOES IT – "CLINICAL DATABASES":

1. Critical Path to TB Drug Regimens (CPTR) – supported by BMGF http://cptrinitiative.org

2. Innovative medicine Initiative (IMI) – supported by EU & Pharma http://www.imi.europa.eu/content/predict-tb

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ISSUES – 1 LACK OF SURROGATE/BIO-MARKERS:

1. Inefficient system to select for candidate regimens for Phase IIIa. Phase II (IIa = EBA, extended EBA; IIb + SSCC, 8-

week Rx) measures only rate of decrease in colony counts; cannot measure sterilizing activity, hence not predictive of relapse rates in Phase III

b. Drug substitution (into standard treatment) as opposed to new regimens (single developer vs. co-development; regulatory issues)

2. Lack of biomarkers for Phase III studies long follow-up

1. 1 + 2 = costs, time, waste (= it takes a lot of time and money to fail!)

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Limited tools to measure & predict

?

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ISSUES - 2:1. Need pharmacologically-driven drug

design/development (PK/PDs) – which requires understanding of MTB metabolism/dynamics + drug PKs & interactions

2. Importance of standardizing study design, esp. core outcome measures, duration of follow-up, non-inferiority margin = 'community of practice'

3. Study design and outcomes for newly-diagnosed vs. chronic multi-drug resistant TB (standard vs. individual-tailored regimens; esp. testing of regimens with newer drugs delamanid, bedaquiline)

4. Importance of PK/PD component in clinical trials5. Clinical data-sharing critical for all the above

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ISSUES - 3:1. Phase III clinical trial complexity:

a. For NDTB: compare to standard 6-month Rx (non-inferiority trial design)

b. 1-2 year post-Rx follow-upc. Numbers required ~800 pts/armd. Total trial duration 6+ years all going welle. Cumbersome for stafff. Expensive

2. Overall clinical trial capacities & capabilities (GCP, GCLP compliant) to absorb Phase 2-3 trials in (highly) endemic countriesa. Merits (and complexity) of sharing investments!b. All public, no-profit, pharma, EDCTP?

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SITUATION ANALYSIS

1. Where are the bottlenecks2. Which ones could be addressed by which form

of open* 3. Tailored solutions4. Who could have the solution; how many steps

away they are

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Bottlenecksthat could

be addressed

through open-source approaches

Target identification:Discovery: Lead identification(hit to lead)

Translation (druggability, non-clinical pharmacology) Development candidate, IND

Development (Clinical Ph 1-3 + CMC + Non-clinical) Registration

Access, Post-marketing studies/surveillance, Intervention & Implementation/Operational research

Harrogate, 30Mar09

Improving R&D EfficiencyTarget identification:

Discovery: Lead identification(hit to lead)

Translation (druggability, non-clinical pharmacology) Development candidate, IND

Development (Clinical Ph 1-3 + CMC + Non-clinical) Registration

Access, Post-marketing studies/surveillance, Intervention & Implementation/Operational research

Models to reliably predict effects in humansIdentify combinations

More efficient regimen selection in PhIISimplified Ph III trialsDevelop combinations

AccessOptimised use in real-lifeData pooling from real-life studies

Share assays, compounds,

data, knowledge

Data pooling, standard m

ethods

Target & compound diversitySuitable screening approaches

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THE LANDSCAPE:Incentives needed to further improve sharing of research data, 30th May 2014 Report commissioned for: Wellcome Trust, MRC, Cancer Research UK and the Economic and Social  Research Councilhttp://www.wellcome.ac.uk/News/Media-office/Press-releases/2014/WTP056505.htmKey findingsa. making data accessible to others can carry a significant cost to

researchersb. funders encourage data access, but data management & sharing plans

they request of researchers are often not resourced adequately, and delivery not monitored nor enforced;

c. very little, if any, formal recognitiond. data managers: vital role as members of research teams, but often low

statuse. the infrastructures needed to support researchers in data

management and sharing, and to ensure the long-term preservation and curation of data, are often lacking

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TDR CLINICAL DATA SHARING :1. Data sharing: facilitation of research through greater access to

data 2. Encouraged by numerous research funders and journal editors

3. Practical expression hampered by technical, cultural and ethical issuesa. When, where and how to share data and who can access and

reuse it for secondary analysis?b. How/Where to store and curate quality database; requires

resources and skilled personal

4. So far no single repository or best practice approach to sharing clinical trial data

5. TDR is exploring this further using TB clinical trial data as working example

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TB R&D OPEN* & DATA SHARING :1. Priority:

a. simplifying, shortening, reducing costs of TB drug R&D; b. develop drug combinations (multiple partners)

2. How:a. Resolving methodological issues b. Sharing information c. (a) cannot happen without (b)

3. Arguments: improved efficiencya. Patients will get more effective treatments soonerb. Economic gain: savings by developers/funding agenciesc. Economic cost of data-sharingd. Balance: G >> C

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Reduce Wastage, duplicationsR&D risks, time, costs

Improve efficienciesIncrease innovation (combine strengths, fill weaknesses of different stakeholders)Create a more conducive ecosystem

TB OPEN* R&D & DATA SHARING

Common understanding of definitions: open-source, open research, data sharing (between whom)Where best applied to R&D path: Pre-competitive' space? Clinical phases?IP?No one-fit-all solution

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HERE THERE

SHARE DATA

DEVELOP METHODS

SHARE METHODS

SHARE OUTCOMES