Lilly Research Laboratories is at the forefront of predictive toxicogenomics work. This area was the focus of intense interest when the field emerged a decade ago. Since then, it has been slow to fulfill its promise.
Craig E. Thomas, Ph.D., senior research advisor, investigative toxicology, suspects the barriers are as much cultural as technological. “As safety assessment in the pharma industry has traditionally been initiated in the latter stages of the discovery process, overcoming the natural fear of failure associated with anything new or unproven is even more daunting.”
“Our feeling is that one of the primary barriers to using transcriptomics predicatively is an inability to put the data into a context that allows decision-making,” said Dr. Thomas.
The challenge for researchers is that with more than 30,000 data points for each microarray, “scientists will undoubtedly see expression changes relative to the controls. What was lacking for many years, however, was an ability to attach toxicologic significance to those changes. For example, is the pattern of gene-expression changes representative or associated with an adverse event?”
Addressing those changes, explained Dr. Thomas, requires developing a large chemogenomics database. During the past three years, Lilly has leveraged DrugMatrix®, a contextual database from Entelos.
“A key feature of having a large database of expression changes integrated with traditional toxicity endpoints is mathematically derived gene signatures that are predictive or coincident with toxicologic endpoints,” he continued. Because the gene signatures are often composed of genes that are not readily associated biologically to outcomes, “you have to believe in the numbers.”
Dr. Thomas said that Lilly’s experience with toxicogenomics has been positive largely because of the contextual database that helped Lilly scientists move beyond purely retrospective studies to study the mechanism of toxicity.
He added that Lilly is unique in focusing much of its toxicogenomics work on in vitro studies, in which gene signatures are used to predict outcomes in animal studies. By addressing toxicology at the hit-to-lead stage, scientists can look across the structure/activity relationship to consider multiple chemical scaffolds.
“Researchers, historically, haven’t considered drug safety at this early stage because the tools were lacking,” he emphasized. The result was often a drug candidate optimized around one scaffold without any toxicology assessment.
“It’s still the early days,” he cautioned, and so the outcomes in long-term toxicology studies of molecules prioritized using genomics in the early preclinical studies remain to be seen. That said, that approach has contributed to a growing pipeline that currently features an all-time high of 50 distinct compounds in clinical development.
The biopharma industry as a whole, however, has experienced less success with predictive toxicogenomics. Only a few validated markers have emerged from this research.
Mark Fielden, Ph.D., senior scientist, Roche, pointed out that the problem reported by the broad industry is that “the biomarkers that have been identified haven’t been robust enough,” for this to be used predictively. But the issue may be with the models used. Roche has experienced success here, said Dr. Fielden, and this remains a ripe area of research.
Other issues outlined by Russell S. Thomas, Ph.D., director of the Center for Genomic Biology and senior investigator at the Hamner Institutes for Health Sciences, included questions of reproducibility, how to interpret the data, and how to build a profile to allow it to become clinically useful.