By Ali Faqi, Ph. D.
The cost of producing innovative, new, and safer drugs is ever-increasing, based on the high rate of attrition during drug development. The risk of unexpected toxicity can be observed at any time during this process or sometimes after marketing approval, thereby leading to the failure of the compound or its withdrawal from the market. Many drugs may fail in late clinical development, when more than 90% of the development costs have already been incurred, causing significant financial pressure on the pharmaceutical companies. Costs to bring just a single drug to the market usually require an investment of hundreds of millions of dollars, sometimes up to a billion dollars, depending on the therapeutic modality. Toxicity is a major contributor to the high attrition rate observed, resulting in about 30% of new drug candidates being terminated because of unexpected animal toxicity profiles or side effects during clinical studies in humans. Therefore, the need to optimize the development path to more quickly identify new therapeutic candidates and minimize their failure rates has become an important task for these companies.
Traditional toxicology studies focus on phenotypic changes in an organism that result from exposure to a drug. This approach does not address altered cellular or molecular patterns that led to the phenotypic changes observed. Therefore, the need for better scientific tools to predict toxicity became highly desirable.
In the past 20 years, many new technologies have emerged that have enhanced current approaches and are leading to novel predictive methods for studying disease risk. An increased understanding of the mode of action and the use of scientific tools to predict toxicity is expected to reduce the attrition rate and thus decrease the cost of developing new drugs. In fact, large pharma companies have began using improved model systems for predicting potential drug toxicity, both to decrease the rate of drug-related adverse reactions and to reduce attrition rates.
One of the more rapidly growing scientific disciplines that can provide insight into the mechanism of action and enable development of targeted cellular assays is the discipline of toxicogenomics. Toxicogenomics is a relatively new field that combines the disciplines of toxicology (the study of potential adverse effects of drugs and chemicals on a living organism) with genomics (the study of all genes in a cell or a tissue at a molecular level, such as DNA, mRNA [messenger ribonucleic acid], and proteins). The term toxicogenomics first appeared in the literature in the late 1990s, and the technology was guided by vendors offering this innovative product to the pharmaceutical industry. In this arena, toxicogenomics focuses on structure/function relationships of the genome as it reacts to exposure from xenobiotics by the application of global mRNA, protein, and metabolite analysis-related technologies to study the effects of hazards on living organisms. Observing the patterns of altered molecular expression caused by specific exposure to drugs and chemicals can reveal how toxicants act and induce disease processes. Identification of toxicity pathways and development of targeted assays to systemically assess potential modes of action will allow a thorough and comprehensive safety assessment. The value of this new technology makes it possible to generate data on large numbers of compounds and exposure scenarios and to develop an extraordinary knowledge base that can be used to guide future research, improve the drug development process, and aid in regulatory decisions. Toxicogenomics is a promising tool and has been applied in several areas of safety assessment. In the face of rapid technological changes, additional opportunities and challenges could arise. Overall, high expectations exist for toxicogenomics to predict potential drug toxicity, to better assess toxicity, and to reduce attrition rates.
Ali S. Faqi, DVM, Ph.D., DABT is the senior director of development and reproductive toxicology (DART) and senior principal study director at MPI Research. He is known worldwide for his DART expertise.