Bridging the translational gap by leveraging brain maps

Healthcare costs associated with brain disorders are steeply increasing, with dementia alone accounting for nearly 1 trillion dollars in the United States. To address this, additional billions of dollars are spent developing new technologies and therapies. Yet, there is an immense gap between experimental and clinical success as evidenced with only ~6% of CNS clinical trials receiving approval to market ("Valley of Death").

Such a translational gap is attributed largely to the heterogeneity of the brain. It means that hundreds of different “organs” (brain regions, cell populations) within the brain may each react differently to medications, with additional variability according to age, sex, and species. However, for most genes implicated in various brain disorders, their expression patterns remain largely unexamined across multiple axes of potential variation, which create enormous challenges in translating research results to the clinic. Simply put, a deeper analysis of human brain expression patterns, when uniformly compared to model species brains, would reveal the commonalities and differences needed to understand translational potential. Thus, earlier assessment of the translational potential of drug targets across species is clear opportunity to improve drug development success.

Here, we’d like to introduce a new way to gauge clinical success potential in drug development by checking the human relevance of research models and drug targets early in the discovery process. With the advent of large-scale brain maps of unprecedented scale and precision, it is now possible to compare the expression patterns of all genes, across hundreds of brain regions and multiple developmental time points in mouse, non-human primate, and human brains, down to the cellular level ("Multi-dimensional Analysis"). The functional outcome of variability can also be inferred by interrogating neural connectivity maps. This integrated knowledge derived from such extensive resources will highlight the most human relevant, thus successful, scientific avenues. 

By leveraging the early stage of drug development process, better and safer study design will be promoted adding additional layers of confidence for drug targets prior to large preclinical and clinical investments. A little "nudge" in the beginning can save a mile down the road. Using this approach, we hope to be able to address questions such as “Where will a drug act in the human brain?”, “Could we predict drug safety in early human development?” or “How can we improve ranking of our drug candidate list?”

Having built and tested various brain maps for the last 10 years, our intimate familiarity with the data sets and expertise in data interpretation allows us to locate yet unrecognized gems in this wealth of data.