Informed toxicity assessment in drug discovery: systems-based toxicology.
Technological advances in the biological, chemical and in silico sciences have transformed many scientific disciplines, including toxicology. A vast new palate of toxicity testing tools is now available to investigators, enabling the generation of enormous amounts of data using only small amounts of test sample and at relatively low cost. In addition to these tools, the pharmaceutical industry has an urgent need for toxicity testing earlier in the process, based on the recognition that safety issues are the single largest cause of drug candidate attrition from development portfolios and the marketplace. However, along with the opportunity provided by new testing tools comes the dilemma of deciding which tools to use and, equally as important, when and why to use them. It may well be unwise to apply a new toxicity test or screening system simply because one can, as both false positive and false negative outcomes can quickly negate the value of a toxicity test system and may even have a net negative impact on drug discovery productivity. This can be true even of test systems that are considered to be 'validated' in the traditional sense. How then is an investigator or drug discovery organization to decide which of the new tools to use, and when to use them? Proposed herein is a strategy for identifying high-value toxicity testing systems and strategies based on program knowledge and informed decision-making. The decision to apply a certain toxicity testing system in this strategy is informed by knowledge of the pharmacological target, the chemical features of molecules active at the pharmacological target, and existing public domain or institutional learning. This 'fit-for-purpose' approach limits non-targeted or 'uninformed' toxicity screening to only those few test systems with high specificity, strong outcome concordance and molecular relevance to frequently encountered toxicity risks (eg, genotoxicity). Additional toxicity testing and screening is then conducted to address specific known or potential toxicity risks, based on existing knowledge of the target pharmacology and secondary pharmacology or chemical attributes with known or suspect risk, and by active 'interrogation' of both the target and active chemical moieties during the drug discovery process. This model for toxicity testing decision-making is illustrated by two case studies from recent experience.
Mayne
James T
JT
Worldwide Safety Sciences, Pfizer Global Research and Development, Eastern Point Road, Groton, CT 06340, USA. james.t.mayne@pfizer.com
Ku
Warren W
WW
Kennedy
Scott P
SP
D000818:Animals; D015195:Drug Design; D004353:Drug Evaluation, Preclinical; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D047428:Protein Kinase Inhibitors / Q000493:pharmacokinetics / Q000633:toxicity; D017367:Selective Serotonin Reuptake Inhibitors / Q000493:pharmacokinetics / Q000633:toxicity; D013329:Structure-Activity Relationship; D049490:Systems Biology; D018675:Toxicity Tests; D014116:Toxicology / Q000379:methods* / Q000639:trends
D047428:Protein Kinase Inhibitors; D017367:Selective Serotonin Reuptake Inhibitors