Biotechnology and pharmaceutical scientists are increasingly relying on high-throughput screening (HTS) methods to discover new leads that may, in turn, be transformed into promising therapeutics.
GEN recently held a Current Trends in High-Throughput Screening roundtable discussion at its offices in New Rochelle, NY. The goal was to obtain the perspectives of two veteran pharmaceutical industry researchers and two instrument and software specialists on the present state of HTS in bioresearch and their views on where the technology might be headed in the future.The following Q&A focuses on HTS trends.
GEN’s Editor in Chief, John Sterling, served as the host for the roundtable discussion. The main participants were Dejan Bojanic, Ph.D., head of lead finding platform, Novartis Institutes for BioMedical Research; Richard M. Eglen, Ph.D., president, biodiscovery, PerkinElmer; Stephan Heyse, Ph.D., head of lead discovery informatics, Genedata; and Berta Strulovici, Ph.D., vp basic research, automated biotechnology head, Merck Research Laboratories.
Sterling: What are the future trends and major challenges in high-throughput screening?
Bojanic: We’re looking at unmet needs. Primary screening is pretty well under control. There’s always room for improvement, but that’s not the principal component. I would say that there is a need for greater diversity in chemical libraries. I think there’s a lot of opportunity there, so obviously we’re always on the lookout for new chemical material that would give us quality starting points.
The characterization of compounds is important, to make sure that we have real actives with well-defined mechanisms of action. In particular, if we’re looking at phenotypic cellular screens, having a clear target-fishing strategy is important. There are more and more black box screens that are being used, and the consequence of that is we can identify activity, but then we have to find out what the actual target is.
Having better downstream capabilities is important as well. Since HTS itself is generally efficient, we need to move that technology downstream so that we can effectively scale-up molecular pharmacology activities.
I think there’s a lot of opportunity for improvement within the disease areas themselves to enhance the iterative synthesis and screening cycles as researchers strive for better quality candidates, and then finally, more appropriate profiling assays that are more characteristic of the potential for side effects in development, particularly at the toxicology stage.
Strulovici: If we look at HTS in the future, the more we work on disease-relevant assays, with all their complexity, the better off we will be. We will also need to validate what we find as much as possible. We do not want to send artifacts to the therapeutics department. I believe, that as HTS scientists, we will have to contribute more than just producing data.
Heyse: It’s interesting to see how the role of HTS centers is changing. What’s even more important is how they integrate into the organization. Many technological challenges, like those involving automation, which were difficult to overcome initially, have been more or less overcome now. As a result, HTS departments get more integrated with a longer section of the discovery pipeline, and get more impregnated by the target biology and disease biology.
So they are moving from technology focused to more biology focused, but also continue to remain as technological excellence groups, holding the expert knowledge in technologies, and diffusing it out to other departments. That’s how I see this age of more pharmacology in HTS— pharmacology diffusing in, technology diffusing out—producing more alignment with other teams. New technologies will be absorbed by HTS departments probably first, and then...
Heyse: Yes, disseminated into the company. So the challenge is to move this forward, keep this very systematic way of working with HTS, and diffusing it out too, as this is the best practice you have for standardized experiments, which then produce defined results, as opposed to lab scientists doing experiments this way today, and another way tomorrow. I think that’s where the challenge lies.
Eglen: From a technology perspective, breaking the bottleneck in lead optimization is a perennial problem. I think that future technologies should start to speak to that aspect of drug discovery. Approaches such as high-content screening or label-free technologies are coming to the foreground now. They will probably find their place in HTS, although I doubt they’ll be a panacea for all the present problems.
I believe that the challenges in screening are really driven by the range of targets that are now entering HTS groups, and by extension, the number and diversity of compounds that now have to be screened—small molecules, biologics, antibodies, or RNAis.
Clearly, the days are gone when technologies would be adopted simply because they were novel, yet proved only to be improvements on the margin. New approaches will certainly have to demonstrate a substantive impact on the demands in HTS, and that will increase the adoption curve in drug discovery.