how big pharma and academia collaborate · project life cycle (small molecule) clinical ph i r...
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1ESC Summer School
How big pharma and academia collaborate ?
Patricia Sansilvestri-Morel
Cardiovascular Research UnitServier Research Institute,
Suresnes, FR
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2A global pharmaceutical company
Servier
A turnover of € 4 billion
Servier’s drugs € 2.8 billion
Generic drugs € 1.2 billion
2nd French pharmaceutical company30th worldwide
3 research centres, including 2 in France,
15 production sites, including 2 in France
25% of turnover excluding generic drugs is invested in R&D
A workforce of 21 000 in 148 countries(4 800 in France)
64 million patients treated daily (Servier’s drugs + generic drugs)
A leader in cardiology
2nd in Europe, 8th worldwide
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Including 22 new molecular entities and 9
Fixed-Dose Combinations (FDC)
4
NEURO-
DEGENERATIVE
DISEASE
Neurodegenerative disease
11
CANCER
Solid tumours and haematological
malignancies
13 (inc. 9 FDC)
CARDIOVASCULAR
DISEASE
Heart failure
1
DIABETES
Type 2 diabetes
4
IMMUNE-
INFLAMMATORY
DISEASE
Autoimmune disease
33 drug candidates in clinical development
OUR R&D IS SPECIALIZED IN 5 MAJOR AXES
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4A NETWORK OF INTERNATIONAL PARTNERSHIPS
Drug Discovery Alliance
Out-Licensing
In-Licensing
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5OPPORTUNITY ROADMAP – CARDIOVASCULAR DISEASE
RESEARCH Preclinical Phase I Phase II Phase III
Heart failure (all forms)Atrial Fibrillation
- Internal Research- Scouting
- Internal Research- Scouting, licensing in
Hypertension, Arrhythmic Cardiomyopathies, Stroke, Hyperlipidemia
- Scouting, licensing in
≈ 50% of R&D projects are developed in partnership
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Hit Finding Lead ID and optim. Preclinical candidate
Clinical Ph II Clinical Ph III Reg. Approuval Pricing Launch
Exploratory
PROJECT LIFE CYCLE(SMALL MOLECULE)
Clinical Ph I
Researc
h
Tolerability
Healthy Volunteers(50)
Tolerability - Efficacy
Small group of patients
(100-500)
Large group of patients
(1000-30000)
Therapeutic utility/ safety
1 y 2.5 y 5.5 y 1-2 y 1-1.5 y
- Animal reg. safety, toxicology,genotox. etc.- Confirm efficacy in largeanimal predictive model(s)- Synthesis scale up- Drug formulationetc…
- Med. Chem. lead ID &optim.- Animal proof of targetengagement (biomarkers)- Proof of concept withsuitable lead cpd.- Preliminary safety studies
- High Throughput Screening- Hit ID
- Target validation (transgenic models…)- Target drugability… - Identification of biomarkers- Dev. screening assays
1 y 4 y 0.7 y1.5 y
5 years
Clin
ical
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Hit Finding Lead ID and optim.
Preclinicaldevt.
ClinicalPh I
ClinicalPh II
ClinicalPh III
Reg.Approuval
Pricing LaunchExploratory
Academia
Start-Ups, Biotech
Middle size/ Big Pharma Industries
Basic Research, early development
Late research through development and early clinical development
All phases, particularly strong from lead optimization through market access
Phase
Player
1
1
2 3
4
1 Collaboration, Licensing, Startup creation
2 Partnering, Licensing to suport financial risk at later stages
3 Asset transfer of promising project from Pharma following strategic portfolio decision
4 Asset transfer due to strategic reasons, mergers, insolvencies etc.
Interactions/transactions
Partners in the pharma ecosystem
Interaction is the key for success
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8Pharma constraints: to have a sustainable system
Key parameters of cost:
Attrition rate (number of project/ drug that failed)
Development stage of the drug when it fails: cost at the end of phase III >> cost during early research
Development duration (Cardiovascular >10 y): cost + patent Development cost (requirement of large morbi-mortality trials)
Key parameters of profit:
Duration of the protection when the drug reaches the market, overall patent duration 20y (EU possibly 5 extra year)
Market size: incidence/prevalence Reimbursement: proportion of patients for which the drug will be reimbursed Labeling: limitations/contra-indications/ black box warning Penetration: competitors/price/perceived medical need/characteristic of the drug Price Cost of goods
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9Evaluation of project value
6-dimension analysis by scoring:
Scientific confidence (key external/ internal data (preclinic/ clinic))
Molecule quality (if applicable)
Developpability (regulatory/development challenges)
Differentiation (versus drugs in development and SoC)
Patients (target population, duration of treatment …)
Project valuation (medical need, peak sale estimation, PoS, patent life)
0
1
2
3
4
Scientific confidence
Molecule quality
Developabilty
Differentiation
Market
Project value
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Research & Preclinical dev.
Cumulative cost
90% of drugs fail to get to Market due to lack of efficacy (>60%) or safety issuesLikelihood of approval for a pre-clinical candidate: 4%
Drug project attrition: How much and why
0.8-1.2B €
Clinical dev.
Bayliss et al., Drug Discovery today, 2016
Launch
Reasons for failure
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To counteract attrition, a critical mass of projects in Research is needed
Drug project attrition: what are the solutions ?
Collaboration between Pharma, Academia and Biotech is the key for success
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Hit Finding Lead ID and optim.
Preclinicaldevt.
ClinicalPh I
ClinicalPh II
ClinicalPh III
Reg.Approuval
Pricing LaunchExploratory
Academia
Basic Research, early development
Strength of academic research
Excellency in basic research -> innovation for new therapeutic targets/ pathways
-> cutting edge of science in determining specific mechanisms of action
-> technical expertise
-> scientific networks facilitating exchanges
The input of academia for innovative therapeutic target remains indisputable
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Hit Finding Lead ID and optim.
Preclinicaldevt.
ClinicalPh I
ClinicalPh II
ClinicalPh III
Reg.Approuval
Pricing LaunchExploratory
Academia
Basic Research, early development
… but academic research must be in phase with Pharma constraints !
Druggability of the targetDuration of a research project : 5 years -> “fast” development of screening assays and hit identification required
Differentiate a pharmacological tool and a preclinical candidate !For ex., chronic treatment needs an orally bioavailable compounds, large scale chemical synthesis transposable for industry, etc…
PatentPatent filing as late as possible ! (just before phase I) allowing a longer duration of the protection when the drug reaches the market
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Hit Finding Lead ID and optim.
Preclinicaldevt.
ClinicalPh I
ClinicalPh II
ClinicalPh III
Reg.Approuval
Pricing LaunchExploratory
Academia
Basic Research, early development
… but academic research must be in phase with Pharma constraints !
DifferentiationA new therapy must differentiate from existing therapies and those in development ! -> Warning with cross talk pathways for instance …
In vivo preclinical modelProof of concept in a predictive and translatable models is the key for success: limitation of failure in late stage development !
Medical needA perception of medical need could be erroneous …
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Medical need for cardioprotection post MI:
Myth or reality ?
Numerous publications describe new targets for reperfusion lesions in patients undergoing PCI
Prevalence and mortality of acute MI are decreasing over timeVery early mortality within 3 months (7.9%) – Low number of CV events following this early phase
-> Short term: medical need IS the prevention of cardiogenic shock/ MODS in selected higher risk patients to limit short term mortality
-> Long term: Prevention of HF/ mortality at long term (>2 y) is a big challenge for a clinical trial (with a race against time for the patent !)
Bui, et al., Nat. Rev. Cardiol., 2010Pedersen et al., JACC, 2014
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16Treatment of Heart Failure remains a high medical need
Hospitalization for HF increases and mortality does not decrease substantially
• Despite optimal treatment, HF prevalence is 2.8%
• Annual mortality of 12% half of HF patients die within 4 years from diagnosis
• Economic and social burden is extremely high
Curative treatment of HFremains a high medical need
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17Research collaboration between Academia and Pharmas
…to be efficient all together !
What is needed to find new treatments in CV diseases:
- Medical need is mainly in HF (all forms) or atrial fibrillation treatment
- Relevant targets should not be modulated by existing treatment
- Proof of target engagement in predictive therapeutic models and/ or genetic models (and ideally in patients !)
- Druggable target
- When preclinical candidates are available, patent should be recent (or ideally not yet filed !)
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18Collaboration Academia/ Pharmas in Research
…to be efficient all together !
What is needed to find new treatments in CV diseases:
- Robust/ rigorous experimental data : increasing number of unreliable scientific publications is a major issue !
• 85% of research resources are wastedCurrently, many published research findings are false orexaggerated (Ioannidis, Plos Medicine 2014)
• 90% of 53 studies were not reproducible.Amgen scientists could not reproduce the findings of 53“landmark” articles in cancer research (Begley exAmgen, Nature, 2012)
• 79% of 67 projects were not reproducedby Bayer scientists trying to reproduce the findings of 67target-validation projects in oncology (Prinz et al., Bayer,Nature Discovery 2011)
Number of retracted articles for specific causes by year of retraction
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Collaboration between Academia and Pharmas is central for innovation
Complementarity of expertise allows a higher efficiency
These links will make it possible to find new treatments for the benefit of patients
Conclusion
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