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The Future of Predictive Biology


By Giacomo Bastianelli

Dec. 2006 / Jan. 2007 | PARIS - Predictive biology, data and the integration of disparate research disciplines are key ingredients for the future of drug discovery research and healthcare, according to speakers at EuroBio 2006, which convened in Paris in late October*.

A major issue in drug discovery is toxicity of drugs. Virtual, or in silico, screening technologies allows teams to select active compounds from large libraries, but it remains a challenge to predict their interactions and toxicity. Lyse Santoro from Ipsen, a European pharmaceutical company, said: "Predictions will not necessarily reduce the time of drug development, but they will help pharmaceutical companies reduce the risks and make the right decisions."

Philippe Manivet is the CSO of BioQuanta, a U.S. company that has a French subsidiary with expertise in in silico technologies. Manivet believes that the challenge of predicting a compound's pharmacokinetic and toxicological profile depends on a source of standardized data. Several databases are available that catalogue molecules and their toxicological profiles, such as the Environmental Protection Agency's Distributed Structure-Searchable Toxicity (DSSTox) database network, despite the lack of standardization. BioQuanta is using multiple sources and standardize data before predicting compound toxicity.

But Manivet cautions that challenges remain in implementing in silico technologies. The major weakness has been reluctance to recognize their limitations and potentials. Only recently have biologists and in silico researchers begun to understand each other's role. Two big challenges in drug design are the introduction of explicit solvent and pharmacophore flexibility in virtual compound screening.

BioQuanta is developing a program of in silico GLP (Good Laboratory Practice), including reproducibility and appropriate controls, which it believes is crucial for the credibility and future of in silico approaches. It will give a new birth to computational biology and chemistry.

ImmunoGrid
Predicting the toxicity and pharmacological properties for small molecules is difficult enough; we are still far from predicting the outcome of an immune response for a specific patient. Computational immunology could eventually provide a dynamic picture of how individual components of the immune system interact to eradicate an infection.

Marie-Paule Lefranc, founder and director of the International Immunogenetics Information System (IMGT), spoke about ImmunoGrid, the Virtual Human Immune System Project. ImmunoGrid is a computer model of the immune system that integrates processes at the molecular, cellular and organ level. Computational models are highly relevant because experimental approaches are expensive, and there are restrictions on the research that can be performed in humans.

Based on IMGT-ONTOLOGY concepts for standardization, and validated with experimental data, the ImmunoGrid  simulator can be used in preclinical and clinical applications of chronic infections, vaccine development and optimisation of immunotherapy protocols.

Giacomo Bastianelli is a PhD Fellow at the Institut Pasteur in Paris.

*EuroBiO 2006: 25-27 October, 2006; Paris, France.

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