Adrian’s Bio:

Dr. Adrian Stevens received his Ph.D. in computational chemistry at the

University of Portsmouth. After his Ph.D., he spent 9 years with BioFocus, a

contract research organization, specializing in small-molecule-based discovery

research. In this time, Adrian worked closely with a broad range of leading

Pharmaceutical companies in collaborative research projects. Following just

over a year at KuDOS, a company specializing in DNA-repair-based pathway

therapeutics and a wholly owned subsidiary of AstraZeneca, Adrian joined

Accelrys in 2008. Adrian is currently the Senior Product Marketing Manager,

responsible for the direction and development of the Discovery Studio product.

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Biological therapeutics are both stored and administrated at a very high

concentration.

Over time, proteins can spontaneously aggregate. In nature, this is a reversible

phenomenon – but synthetic antibodies tend to do this irreversibly.

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Large pharmaceutical acquisitions and mergers over the last 5-6 years include:

MedImmune Inc. and Cambridge Antibody Technology (CAT)

acquisitions by Astrazeneca in ca. 2006

Genentech acquisition by Roche in 2009

Wyeth acquisition by Pfizer in 2009

Genzyme acquisition by Sanofi-Aventis in 2011

Target users are computational biologist and, potentially, biological formulation

scientists, discovery scientists, immunologists and biologists

The Market is Biotherapeutics within the Life Sciences industry; sspecifically,

monoclonal antibodies (IgG1)

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Protein therapeutics, e.g. antibodies, are becoming increasingly important.

Protein aggregates more easily at high concentration. This is important,

because they are both stored and typically administered at high concentrations.

Predicting the aggregation propensity of a therapeutic protein is important in

several stages of drug development:

Early screening – high throughput

Protein engineering on a specific target, such as humanization of an

antibody

Formulation

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Every day that you have to spend in formulation prior to aggregation is at a very

high cost. Previously, the only way you can identify the likelihood of clumping

was through 6 – 8 weeks of experimental science. This is the first method of

predicting aggregation that’s validated and proven.

One of the FDA requirements with a new biologics for the market is showing the

experiment, but with this, you can work out at a much earlier stage what

antibodies are going to work and limit experiment time / cycles.

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The speed improvement is a result of commercial software development know-

how and does not result in any loss of precision or predictive accuracy. Moving

from 24hrs to 2mins per calculation puts the prediction into near real-time study

workflows. This is a huge benefit to the design workflow. As well as the obvious

speed improvements, the integration of the algorithm into the design workflows

affords the commercial users significant added value. Once you know where

your site of aggregation is, you can look at modifying the residues to reduce the

propensity. However, that could inadvertently result in reduced protein stability,

or worse, loss of efficacy.

By including the aggregation code into wider design workflows, like protein-

protein docking, thermal and mutational stability, the user can make highly

informed decisions on what change to make, without risking the stability or

efficacy of the biologic.

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Discovery Studio is the most comprehensive software solution for Life Sciences

customers.

For Biotherapeutics customers, a fast growing market, we have led the way in

delivering both classical discovery tools like homology modeling and loop

refinement, through to solutions for industry-specific challenges, such as

protein binding, protein stability and protein aggregation prediction. Uniquely,

DS is applicable in this market to both discovery and early stage development

researchers.

No other product has such broad scope or extensive tools for biotherapeutics

customers.

Discovery Studio is a key application in the Modeling and Simulation pillar of

the Accelrys Enterprise R&D Architecture.

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