lead optimization in drug discovery

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The challenge for lead optimization is to improve the properties of compounds in the lead series. Those properties include potency and efficacy, properties related to PK (like permeability and solubility), and properties related to safety (like hERG binding and target selectivity). We can demonstrate this idea with a radar plot. The greater the area within the plot, the more optimized the lead has become. These improvements in properties are achieved through structural modification of the lead. Let’s generalize how these optimizations are achieved.
A typical optimization program relies initially on in vitro studies. New analogues within a lead series are prepared and tested rapidly in in vitro assays that monitor potency, ADME properties, and safety. Once the in vitro properties have been improved to an adequate level, the most promising compounds will be studied in vivo in a preclinical animal species. PK studies are normally performed first to ensure that adequate exposure can be achieved in the plasma by the selected route of administration. Efficacy studies will follow, often with simultaneous monitoring of safety biomarkers. Data from the in vivo studies will guide another round of optimization that will culminate in another in vivo study. This is a highly iterative process with feedback driving future decisions.
A lead’s in vitro properties do not need to be perfect, and even a flawed lead may be studied in vivo. Early in vivo data, even on a lead that is known to be flawed, helps validate the research plan and supports additional research effort. Part of validating the research plan is making sure that the in vitro assays are predictive of in vivo activity. This idea is called in vitro-in vivo correlation or IVIVC, though the acronym IVIVC is most frequently associated with PK properties. Because in vitro assays tend to be quick and relatively easy to perform, relying on in vitro assays as much as possible during lead optimization is preferable. Of course, the value of in vitro assays is only realized if the results from in vitro assays agree with outcomes of the in vivo studies. Confirming agreement between in vitro and in vivo studies is an important part of lead optimization. Let’s give an example.
Let’s assume we are working in a drug program with the goal of developing an oral drug. We have an early lead with great potency, good signs of safety, but poor membrane permeability. Of course, low permeability would be a real problem for an oral drug. Although the lead has low permeability, it would be worthwhile to test the lead in vivo with IV dosing. So, the IV dosing will bypass the need for good oral bioavailability. The discovery team would gain confirmation into the in vivo efficacy and safety of the lead series, as well as other PK information, such as the half-life. The team might also learn about the selected animal disease model, such as which biomarkers are most informative. The information from such a study may inform additional changes within the lead series beyond just addressing issues around membrane permeability.