Adverse effects of drugs pose potential harm to patients and can hinder or halt the development and intended therapeutic use of a drug. Such effects can arise from primary pharmacology (‘exaggerated pharmacology’, or unintended effects in non-targeted organ systems), secondary pharmacology (i.e., at another receptor, related or unrelated to the primary target), or from the effects of a drug metabolite acting at the primary target for the parent drug and/or at an off-target receptor (Jenkinson et al., 2019). In this blog, I’ll explain how Secondary Intelligence™ software can allow researchers to automate, streamline, and standardize secondary pharmacology analysis and increase confidence in critical go/no-go decisions.
When adverse effects arise from the primary target, pharmaceutical companies must either manage the risk or abandon the target altogether. However, off-target safety issues provide an opportunity to select compounds without such activity or modify the chemistry to eliminate the interaction. While side effects related to the primary target may be unavoidable, there is always a work-around with respect to off-target safety. And by minimising off-target promiscuity, you reduce the chances of failure (Bowes et al., 2012).
Best practices in assessing off-target drug interactions.
Secondary pharmacology is typically assessed by screening compounds against a panel of receptors representing various drug target classes, including G-protein coupled receptors (GPCRs), ion channels, enzymes, kinases, nuclear hormone receptors and transporters. GPCR readouts are measured using ligand binding assays, providing Ki values, while other assays, mostly cell-based, provide IC50 values. Some pharma companies first screen at a fixed concentration (e.g., 10 μM) and only go on to generate Ki or IC50 values where there is >50% inhibition (a ‘hit’). After determining the Ki or IC50, a sensible next step would be to use a functional assay to determine whether the test compound is a positive modulator (e.g., agonist) or a negative modulator (e.g., antagonist) at the receptor.
Upon receiving the screening panel readout, the secondary pharmacology expert must rely on their expertise, judgment, and available literature to evaluate the significance and relevance of the interactions for the compound in a clinical setting. The key question is whether these off-target interactions will occur at clinically relevant exposures, and if they represent a concern for the intended patient population.
Interpreting safety readouts
The secondary pharmacologist faces a challenging task of making critical judgment calls relatively quickly. They must consider the pharmacodynamic effects associated with the interaction with a specific receptor across multiple organ systems and the level of receptor occupancy (as an agonist or antagonist) necessary to generate adverse effects.
There is no guidance on the total number of receptors to screen with the FDA receiving an average of ~74 receptors in IND submissions (Scott et al., 2022). As part of our efforts to address this, we have recently completed a qualitative and quantitative evaluation of 100 receptors, including the influential ‘Bowes panel’ of 44 receptors selected by 4 major pharma companies based on hit rate and safety implications (Bowes et al., 2012).
For each receptor, we compiled a list of the marketed drugs (and any non-marketed drugs with clinical data) that target that receptor for their therapeutic efficacy (‘reference drugs’). Agonist and antagonist drugs were evaluated separately. Then we listed the pharmacodynamic / therapeutic effects (main desired effects) and adverse effects in common for that list of drugs. (Remember that a desired effect for a drug targeting, say, β2-adrenoceptors for its therapeutic benefit may be an adverse effect for a drug that isn’t, if it hits this receptor as an off-target.) Then, for each drug, we sourced the lowest dose and corresponding plasma concentration causing the pharmacodynamic / therapeutic effects. Finally, after converting that value to an unbound plasma concentration (Cu) from its plasma protein binding data we divided it by the Ki (or IC50) for that reference drug at that receptor (Cu/Ki). Then repeated the process for all marketed drugs targeting that receptor.
Secondary Intelligence: A tool to help make critical drug development decisions.
By simply uploading the screening panel readout and predicted human plasma Cmax (unbound) of your compound in Excel, our Secondary Intelligence™ software tool can provide valuable insights. If its Cu/Ki ratio falls within the range observed for reference drugs targeting a specific receptor, this suggests a likelihood of experiencing side effects associated with that receptor interaction during clinical use of the compound. However, if the ratio is below that range, then the further away from that cluster of reference drugs it lies, the less likely it is that you will see those side effects. There is the option of a traffic lights approach, whereby if the ratio lies less than, say, one-tenth of the lower end of the range of reference drugs, then this receptor engagement is unlikely to be clinically significant, and would get a ‘low likelihood’ rating, whereas if it fell between the two (within one-tenth of the lower end of the range of reference drugs) it would be assigned a ‘medium likelihood’ rating.
Furthermore, our software tool provides a comprehensive list of the most common side effects, expected safety pharmacology outcomes, and translatable biomarkers for each receptor. Drugs and research compounds selective for each receptor are listed with links to further information on them. Additionally, we have developed over 200 Mechanistic Safety Pathways (MSPs) following the Adverse Outcome Pathway (AOP) format, offering a concise mechanistic understanding of the adverse effects, supported by key publications.
Secondary Intelligence™ is a tool that has already done the heavy lifting for you. It not only allows you to interpret safety assay readouts quickly but also ensures a consistent approach. When faced with questions such as the likelihood of engaging off-target receptors during clinical use, expected side effects, and underlying mechanisms, you can provide a credible and evidence-based response with just a few mouse clicks. Additionally, the tool can be used ‘in reverse’, to reveal off-target mechanisms responsible for safety findings encountered in nonclinical, in vivo studies and in human clinical trials.
Here’s a short (~3-minute) video that provides a summary of what it does:
Secondary Intelligence™ is available by purchasing an annual software license or via our expert consultancy service. Connect with a member of our team to learn more about how Secondary Intelligence™ can support your drug development initiatives.
References
Bowes J, Brown AJ, Hamon J, Jarolimek W, Sridhar A, Waldron G, Whitbread S. (2012) Reducing safety-related drug attrition: the use of in vitro pharmacological profiling. Nature Reviews Drug Discovery 11:909-922.
Jenkinson S, Schmidt F, Rosenbrier Ribeiro L, Delaunois A, Valentin J-P. (2020) A practical guide to secondary pharmacology in drug discovery. J Pharmacol Toxicol Methods 105:106869.
Scott C, Dodson A, Saulnier M, Snyder K, Racz R. (2022) Analysis of secondary pharmacology assays received by the US Food and Drug Administration. J Pharmacol Toxicol Methods 117:107205.
