from personalized to precision & predictive medicine: in silico models of patients and diseases
TRANSCRIPT
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From Personalized to Precision & Predictive Medicine:
in silico models of patients and diseases
Andrea R. BeccariDrug Discovery Platform ManagerAssociate Researcher National Research Council (CNR)
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11 October 2016, European Parliament Brussels
In Silico – turning Big Data into Personalized Medicine
© 2015 Dompé farmaceutici S.p.A.
All rights reserved. Confidential and proprietary.www.dompe.com
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“ There are no incurable diseases — only the lack of will.
There are no worthless herbs — only the lack of knowledge ”
“ Medicine is the science by which we learn the various states of
the human body in health and when not in health, and the means
by which health is likely to be lost and, when lost, is likely to be
restored back to health.
Medicine in other words, it is the art whereby health is conserved
and the art whereby it is restored after being lost. “
Avicenna
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2 million deaths in Europe due to cardiovascular diseases costing €192 billion
27 million people suffering from diabetes and 120 million with rheumatic and musculoskeletal conditions with large cost implications
Brain disorders cost an estimated €800 billion In England treatment of Alzheimer’s disease costs approximately £17
billion
Source: European Commission |data presented during the Workshop on "HighPerformance Computing (HPC) in Health Research” inBrussels, 1st of October, 2014
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Costs of Pharmaceutical Research and Development
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31 34 38 39 40 44 48 50 56 6
5 69 75 8
4 95 1
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Industry R&D spending
Industry R&D spending (US$ billion)
2521
29
53
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3035
27 2417
21
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18 18 1621 19
15
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3325
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FDA drug approvals 1993-2013
NCE BLA Total
1 Drug = 5.5 bio$
11 October 2016, European Parliament Brussels
In Silico – turning Big Data into Personalized Medicine
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Efficacy of Pharmaceutical Research and DevelopmentClinical Phase success rate
Diagnosis and treatment of illness arecurrently performed on the basis of
clinical protocols designed for ageneral disease definition and not aparticular responding population.
The outcome is 9 out of 10 failure dueto:
Lack of Efficacy in >50%
Lack of Safety in >10%
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7
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Nature Biotechnology Volume: 32, Pages:40–51 (2014) DOI:doi:10.1038/nbt.2786
11 October 2016, European Parliament Brussels
In Silico – turning Big Data into Personalized Medicine
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A successful drug in detailsEtanercept: a breakthrough disease modifying biological drug
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J Rheumatol. 2001 Jun;28(6):1238-44 | Long-term safety and efficacy of etanercept in patients with rheumatoid arthritis
2%
7%
37%
32%
23%
0%
5%
10%
15%
20%
25%
30%
35%
40%
No Effect Discontinued <50% >50% 100%
Safety and Efficacy of Etanercept (Enbrel) This is an emblematic example of the
actual pharmaceutical research is
reductive.
The model “one target” – “one drug” is
insufficient to address both the disease
complexity and the patient’s peculiarity.
So to obtain an effective treatment of a
disease we need a wider knowledge of
the pathological condition to validate
mechanistic and predictive disease
modelsRescue
11 October 2016, European Parliament Brussels
In Silico – turning Big Data into Personalized Medicine
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The need to increase knowledge is greater than ever
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Stand alone public or private research entities cannot achieve the required level ofknowledge need to address the multifactoriality of the pathology and the patientspecificity
Need for unified frameworks to support data collection, re-use and modelling combined with establishment of protocols to ensure model verification & validation
In this direction the EMA initiative clinical data publication policy take place.
EMA creates a single repository of all the clinical studies conducted in Europe collectingall the data at patient level and allowing public and private research entities to performmeta analysis and identify more effective patient’s stratification.
Is complelling to extend such initiative to all relevant certified clinical data with theaim to collect, organize and redistribute them
11 October 2016, European Parliament Brussels
In Silico – turning Big Data into Personalized Medicine
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The need to increase knowledge is greater than ever
In addition to the collection of clinical data, the identification of genetic predisposition,and transcriptomic signature of pathologies is fundamental for the real implementationof precision medicine.
Initiative seek to scale up population-based genome sequencing and integrate it withclinical data:
• UK 100,000 Genomes Project
• US Precision Medicine
This initiatives are examples of actions taken in order to profile populations forpatients stratification and disease prediction.
But we’ll increase knowledge only if we’ll be able to combine “ big data analytics” withmechanistic modelling
8 11 October 2016, European Parliament Brussels
In Silico – turning Big Data into Personalized Medicine
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From knowledge to Predictive Medicine
Such collected data (clinical and genomic and transcriptomic) have to train and feed insilico models to obtain computational models of pathologies comprehensive ofdifferent patient’s sub-populations representative of the each pathological condition.
Is fundamental to recognise the potential of in silico approaches in healthcareand apportion significant funding to support its routine implementation
Remarkable initiatives like Virtual Physiological Human can give the theoretical andinfrastructural framework for the development of predictive medicine by the use of insilico clinical trials. Driving the training and development in skills needed to deliver insilico routinely
9 11 October 2016, European Parliament Brussels
In Silico – turning Big Data into Personalized Medicine