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.

Dual-action hypoglycemic and hypocholesterolemic agents that inhibit glycogen phosphorylase and lanosterol demethylase.

Diabetic dyslipidemia requires simultaneous treatment with hypoglycemic agents and lipid-modulating drugs. We recently described glycogen phosphorylase inhibitors that reduce glycogenolysis in cells and lower plasma glucose in ob/ob mice (J. Med. Chem., 41: 2934, 1998). In evaluating the series prototype, CP-320626, in dogs, up to 90% reduction in plasma cholesterol was noted after 2 week treatment. Cholesterol reductions were also noted in ob/ob mice and in rats. In HepG2 cells, CP-320626 acutely and dose-dependently inhibited cholesterolgenesis without affecting fatty acid synthesis. Inhibition occurred together with a dose-dependent increase in the cholesterol precursor, lanosterol, suggesting that cholesterolgenesis inhibition was due to lanosterol 14alpha-demethylase (CYP51) inhibition. In ob/ob mice, acute treatment with CP-320626 resulted in a decrease in hepatic cholesterolgenesis with concomitant lanosterol accumulation, further implicating CYP51 inhibition as the mechanism of cholesterol lowering in these animals. CP-320626 and analogs directly inhibited rhCYP51, and this inhibition was highly correlated with HepG2 cell cholesterolgenesis inhibition (R2 = 0.77). These observations indicate that CP-320626 inhibits cholesterolgenesis via direct inhibition of CYP51, and that this is the mechanism whereby CP-320626 lowers plasma cholesterol in experimental animals. Dual-action glycogenolysis and cholesterolgenesis inhibitors therefore have the potential to favorably affect both the hyperglycemia and the dyslipidemia of type 2 diabetes.