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• Harness the added value of QSP

• Define, accelerate and ensure confidence in decision making

• Power the predictability of drug discovery and development

SPEAKERPACK

JANUARY 27TH-29TH 2015

This speaker pack compiles the expert views of:

RON BEAVER, Founder, Chairman & Chief Executive Officer, ROSA & CO.

DEAN BOTTINO, Oncology Clinical Translational M&S Leader, MILLENNIUM

SAROJA RAMANUJAN, Sr. Scientist, Group Lead, GENENTECH

JOHN BURKE, President & CEO, APPLIED BIOMATH, LLC

The following thoughts and discussions provide excellent insight into some of the greatest opportunities and challenges in the QSP space.

Harnessing the added scientific value of QSP is a real challenge but the following should give some context and examples of how this can be achieved.

WELCOME TO QSP CONGRESS 2015: There is no better time than now to invest in Quantitative Systems Pharmacology and QSP Congress 2015 has brought together the leaders who have so far constructed and defined this burgeoning field.

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Dean Bottino, Oncology Clinical Translational M&S Leader, Millennium

WHAT DO YOU SEE AS THE BIGGEST CHALLENGE TO THE WIDER AND SUCCESSFUL ADOPTION OF QSP?

The main challenge with QSP is to make sure the term doesn’t get co-opted just to re-brand what some of us have been doing for the past 10 years. For QSP to be a meaningful term, it has to bridge the disciplines of systems modelling and pharmacometrics, that is, it has to combine biological interpretability with some level of statistical rigour and timely insights.

Proof of consistent critical impact on projects that justifies the resource requirements; development and standardization of technical approaches to allow rigorous evaluation of and thereby confidence in models and model-based predictions.

Ron Beaver, Founder, Chairman &

Chief Executive Officer, Rosa & Co.

Saroja Ramanujan, Associate Director, Group Lead, Genentech

John Burke, President & CEO,

Applied BioMath, LLC“

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To achieve a broad recognition in the pharmaceutical and biotechnology industries that QSP is essential to the efficient and cost effective development of any drug candidate, beginning in the early stages of preclinical development.

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Finding talented new hires and convincing senior management to move away from using their gut feeling to make decisions, but rather employ systematic and quantitative techniques

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Dean Bottino, Oncology Clinical

Translational M&S Leader, Millennium

WHERE ARE THE TYPICAL QUESTIONS QSP CAN ANSWER FOR PHARMA PROJECTS?

In my view QSP can answer similar questions as pharmacometrics aims to address, but can do so in a way that is more convincing to clinicians and biologists and more “extrapolable” than empirical and “semi-mechanistic” models because the parameters are biologically interpretable.

Identification or evaluation of new or novel targets, clarifying complex mechanisms of action, identification of potential biomarkers, segmentation of patients (e.g., responders vs. non-responders), assessing competitive differentiation, design of informative studies and evaluation or design of ideal pharmacologic properties.

Ron Beaver, Founder, Chairman & Chief Executive Officer, Rosa & Co.

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“ Target prioritization, compound requirements, hypotheses or critical pathways for response, dose/regimen questions, combo Rx considerations, and predicted patient subset responsiveness.

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Saroja Ramanujan, Associate Director,

Group Lead, Genentech

Dean Bottino, Oncology Clinical Translational M&S Leader, Millennium

CAN YOU GIVE AN EXAMPLE OF WHEN A QSP APPROACH HAS DELIVERED ADDED VALUE?

Some work we did at Novartis about 5 years ago used a simplified “PK-pathway-PD” model to understand and characterize paradoxical activation of a cancer pathway by our study drug. The model was used to extrapolate the pre-clinical observations into a clinically relevant parameter range and ultimately contributed to a decision to halt development of that agent.

Using QSP approaches following a phase 1 study in healthy volunteers to assess feasibility. A liability was found using systems approaches. The modeling was used to influence management to discontinue the lead, and a back-up candidate was identified using the model defined best-in-class criteria to be accelerated into clinical trials. This saved ~ $100m in clinical trials for the inferior molecule.

John Burke, President & CEO,

Applied BioMath, LLC

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While there are classic examples, the details of many I know of are confidential, which is one of the challenges to proving the past impact of QSP. For example, one great example is when a major pharma company worked with the organization Entelos to evaluate a very “hot” target in diabetes. QSP based predictions indicated that despite promising results in rodents, the target would not work in humans, and the modeling effort explained the biological rationale as to why this would be the case. As a result, the pharmaceutical company did not continue work on the target. Multiple other pharma since did and so far, have failed to show efficacy. This example of a “NO GO” translates into significant savings of the $ that would have been invested in clinical trials.

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Saroja Ramanujan, Associate Director, Group Lead, Genentech

Dean Bottino, Oncology Clinical

Translational M&S Leader, Millennium

WHERE DO YOU SEE THE FIELD OF QSP IN 5 YEARS TIME – WHAT NEED TO BE ACHIEVED TO GET THERE?

I hope in 5-10 years two major transformations will have taken place. First, ‘classical’ pharmacometricians will be using more biologically-inspired structural models, for example feedback loops rather than sums of sine curves to generate circadian rhythms (to the extent that doing so is relevant to the question being asked). Second, ‘classical’ systems modelers will be more sophisticated users of parameter estimation and possibly nonlinear mixed effects modelling, so that they can embrace population heterogeneity and parameter uncertainty and communicate the uncertainties in their predictions to decision makers.

QSP approaches will be applied in tandem with bench and clinical research and used systematically for virtually all drug candidates, beginning in preclinical development and applied iteratively throughout the entire drug development process. To get there requires, for example, delivering value in a timely, credible fashion in any application, and a deliberate long-term approach to adoption within each organization and in the broader industry.

In 5-10 years, I hope that QSP approaches will be the standard in industry, not only in late stage clinical trial support, but throughout the drug discovery processes. This would be no different than using mathematics, HPC and (bio)physics in mechanical engineering, electrical engineering, or computer engineering, for example, to optimize design, maximize value, and act as an interface between the hard sciences and humanity, but here for drug discovery. If this could be achieved, then there would be a reducing in late stage attrition, perhaps drug costs would be reduced, and better drugs would be designed for the right patients. We’ll need quite a few success stories and very few failures in industry. As with other disciplines in the past, we do not have the comfort and time to fail, so we cannot over promise or over sell what we can do. We’ll need the right leadership and the right workforce from academia.

Ron Beaver, Founder, Chairman & Chief Executive Officer, Rosa & Co.

John Burke, President & CEO, Applied BioMath, LLC

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“ I expect to see it as a more common and recognized approach within pharma, not just a one-off. I still do not expect it to be applied to every drug project, nor should it be necessarily. I would expect to see some sort of QSP group/effort in all major pharma companies. I expect to see a greater understanding of QSP in the pharmacometrics community. Requirements for this are essentially overcoming the obstacles stated in response to Question 1 above.

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Saroja Ramanujan, Associate Director,

Group Lead, Genentech

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Registerwww.qsp-congress.com/register

Tel: +1 212 537 5898

Email: register@hansonwade.com

Quantitative Systems Pharmacology (QSP)

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Improve Decision Making with More Holistic & Precise Understanding

of Complex Disease Systems & Pharmacologic Interventions

EXPERT SPEAKERS INCLUDE:

LEAD PARTNER:

Peter Sorger

Professor, Systems

Biology Harvard Medical

School

Gianluca Nucci

Vice President, PTx,

Clinical Pharmacology

Pfizer

Jeff Barrett

Vice President, Global

Head, Interdisciplinary

Pharmacometrics

Sanofi

Sandra Allerheiligen

Vice President,

Quantitative

Pharmacology &

Pharmacometrics

Merck

Richard Okita

Program Director,

Pharmacology, Physiology

& Biological Chemistry

NIH

Megan Gibbs

Executive Director,

Site Head, Quantitative

Pharmacology

Amgen

Andrea Califano

Professor, Chemical

Systems Biology

Columbia University

Ron Beaver

Founder, Chairman &

Chief Executive Officer

Rosa & Co

Eric Sobie Associate Professor,

Pharmacology &

Systems Therapeutics

Icahn School of

Medicine at Mount

Sinai

RESEARCHED & DEVELOPED BY:

Tel: + 1 212 531 5898 | Email: join@hansonwade.comwww.qsp-congress.com

This conference will be the first to comprehensively explore

the current state and future directions for QSP, with topics

ranging from its role in the scientific process, typical applications,

methods to qualify QSP models, proven approaches to accelerate

organizational adoption, and future trends Rosa & Co

QSP Congress 2015

January 27th-29th 2015 | Boston, MA

JANUARY 27TH-29TH 2015