The Ferryman

Computer-based Predictive Toxicology: Advances and Impact of Cheminformatics on the Safety-oriented Design of New Products

Current advances in computer-based predictive toxicology offer the potential to create more advanced environments for the screening and prediction of safety issues due to chemical and drug adverse side effects, drug-drug and chemical-system interactions, and chemical and drug toxicologies in the environment and the human body.  Advances in this growing field also offer the potential to replace or reduce the need for animal testing and to reduce later stage clinical trial failures or new product development rejection. Acceleration of progress in practical applications requires the creation of interoperable environments, knowledge sharing, data integration, algorithm development, and extensive validation and testing. 

Numerous opportunities exist in this field for scientific advances, but also for innovation, service and product development, and value creation. Additionally, significant collaboration approaches are a scientific, industry and society imperative to advance this field and the safety of new products and all society members.  Collaborative approaches need to support the multidisciplinary networking and collaboration between computer scientists, biologists, chemists, toxicologists, product development and clinical and environmental researchers, and to network groups, centers, initiatives, projects and data into interoperable semantic frameworks, systems, knowledge bases and virtual organisations.

At our Predictive Toxicology session chaired by Artem Cherkasov (University of British Columbia) running 17 October 2008 at Bryn Mawr recent developments in the field of predictive toxicology will be presented and discussed.

The session will be preceded the evening of October 16 by a Knowledge Café to discuss Collaboration Opportunities in Predictive ADME & Predictive Toxicology.

A description of the session with presentation abstracts follows.  Please add your comments, discussion or questions at the end of the post.

Predictive Toxicology

http://innovationwell.net/COMTY_confprogr08predtox

(Please follow continuation here to read abstracts.  Comments can be made at the end.)

Predictive ADME: guiding the lead development and optimization process

The prediction of absorption, distribution, metabolism, and excretion (ADME) properties has become increasingly important as failures late in the drug discovery process become more costly. Increasingly, stringent in vitro and in vivo requirements have been placed on the hit-to-lead and lead optimization stages of the drug discovery process. Although it is tempting to dismiss ADME modeling and simply conduct an in vitro or in vivo experiment to get “the correct answer”, this approach is not practical. A skilled, competent medicinal chemist working on a lead optimization program can easily conceive of far more compounds than can reasonably be synthesized during the time of a lead optimization effort. In vivo studies are expensive and time-consuming and may become the rate-limiting step for some projects, particularly for small pharmaceutical companies. Rather than providing “the correct answer”, modeling provides a means of “stacking the deck” in favor of the medicinal chemistry effort, increasing the likelihood that a given compound will show the desired effect in vitro or in vivo.

At our Predictive ADME session chaired by Anthony Klon running October 16 at Bryn Mawr recent developments in the predictive modeling of ADME properties will be presented and discussed. Speakers will present their research into modeling microsomal stability, drug-drug interactions, and membrane transport processes such as blood-brain barrier penetration, intestinal absorption, and skin penetration. One topic of the accompanying discussions will be the appropriateness of relevant biological endpoints for ADME/PK modeling.

The session will be followed in the evening by a Knowledge Café to discuss Collaboration Opportunities in Predictive ADME & Predictive Toxicology.

A description of the session with presentation abstracts follows.  Please add your comments, discussion or questions at the end of the post.

Predictive ADME

http://innovationwell.net/COMTY_confprogr08adme

(Please follow continuation here to read abstracts.  Comments can be made at the end.)

Computational Biology: Data Mining in Biomedical Research

Biomedical research, be it in the biopharmaceutical industry, academia or governmental laboratories, is becoming an information driven science. An enormous amount of data is either present in published literature and patents or being generated using high-throughput technologies (such as DNA sequencing, microarrays, genome-wide association, proteomics etc.). The resulting computational biology challenges currently involve the development of intelligent data mining methodologies for these high-dimensional data and the development of databases that facilitate the hosting and integration of these diverse data-sets. The computational advances being made in these areas are significantly impacting biomedical research ranging from fundamental biological findings that relate genes and environment to disease all the way to molecular biomarkers for drug efficacy or toxicity.

In our InnovationWell session chaired by Debraj GuhaThakurta (Rosetta Inpharmatics, Merck & Co.) taking place 14 October 2008 at Bryn Mawr, we have gathered a set of top researchers who have significant experience in the areas of data mining and integration. Presentation and discussion topics will include: molecular network reconstruction from genetically segregating populations (Paul McDonagh), the use of molecular networks for environmental risk assessment (Stephen Edwards), semantic web technologies for modeling biological pathways (Christopher Bouton), application of integrated genomics and genetics in pharmaceutical discovery (Debraj GuhaThakurta), and comparative genomics in drug discovery (James Brown).

A description of the session with presentation abstracts follows.  Please add your comments, discussion or questions at the end of the post.

Computational Biology

http://innovationwell.net/comty_confprogr08compbio

(Please follow continuation here to read abstracts.  Comments can be made at the end.)

Knowledge Management in Translational Medicine

Healthcare is a highly complex, information-driven industry, and effective knowledge management is at the heart of the drug discovery and development process. Translational medicine is becoming increasingly important within the pharmaceutical industry where it is defined by a variety of initiatives designed to facilitate the transfer of knowledge from the bench to the bedside and back.

On the 15 October 2008 at the InnovationWell Community of Practice Meeting at Bryn Mawr College, Philadelphia, I will chair a day-long session where we have brought together a diverse set of speakers representing a broad spectrum of activities across the pharmaceutical workflow – from target identification to clinical trials. Each presentation will describe specific examples of advances in translational medicine brought about by practical approaches to improved knowledge management. Sometimes these advances will be technology-based, sometimes they will have resulted from innovative forms of collaboration and the use of Web 2.0 tools. Together we hope these speakers will stimulate discussion and the transfer of insights and ideas illustrating the potential of knowledge management tools and techniques to drive advances in translational medicine.

A description of the session with presentation abstracts follows:

Knowledge Management in Translational Medicine

http://innovationwell.net/COMTY_confprogr08kmtransmed

(Please follow continuation here to read abstracts.  Comments can be made at the end.)