Speeding Up the Process
So what role does high-content screening play when it comes to drug discovery? In theory, technology that pole vaults over in vivo and in vitro testing of vast numbers of compounds should go a long way toward optimizing the discovery process, saving time and money. However, in silico results are not definitive, since they do not cover a plethora of factors that influence the fate of a project. These include biophysical properties of the compound, strategic and safety issues, and, frequently, IP considerations.
Bender argued that “high-content imaging fares rather well when it comes to the success of HTS campaigns, and potentially, by integrating in silico tools such as ligand-target prediction, those campaigns may fare even better in the future.”
Delphic prophesies predicting breakthroughs in drug development using in silico modeling technologies abound.
A recent Deloitte report, The Changing Face of R&D in the Future Pharmaceutical Landscape, bemoans the current state of the pharmaceutical industry and predicts that companies will exploit “virtual R&D processes with significant outsourcing to maximize flexibility and manage development risk.”
While in silico modeling holds much promise, it still remains an unproven technology, as there are no drugs that have traveled the epic voyage from lead compound optimization to the marketplace. A number of anti-HIV drugs have been developed through programs that include in silico modeling, however.
As pharma companies are understandably reticent to reveal the details of their discovery programs, it is not surprising that the precise role of in silico modeling in drug development is somewhat opaque. Moreover, the very long gestation period required in today’s world of drug development means that new strategies may take years to see their effects realized. With many small and large players in the field, the next few years should see the vindication of this approach.