Open innovation, early safety assessment and better lead optimization are drivers for drug development success

The 18th Annual Drug Discovery Summit in Berlin, held June 12-13, gathered many players from the pharmaceutical landscape to focus on drug discovery challenges including validating novel drug targets, screening strategies and improving lead optimization in different therapeutic areas. Many presentations discussed the modern medicinal chemistry strategies, computational chemistry, phenotypic and target-based screening, artificial intelligence, open innovation, and drug safety. I found three key notes highlighted during this very exciting conference.


Accelerating lead optimization with better starting point and faster decision making process

When a “hit” is identified, medicinal chemistry derives hundreds of compounds with slight changes in molecular structure to get the highest potency and best physiological profile for the drug candidate before entering preclinical testing. The lead optimization phase currently faces opposite constraints: more and more stringent criteria are required for a molecule to effectively become a drug candidate – to maintain chances of success – while time to develop it must decrease to keep a strong innovation pace. Solutions exist to address this apparently difficult equation. The first solution includes starting with better hit identification which makes easier the lead optimization. Screening of chemical series must be rational in order to exclude fragments or chemical structures that are known to lead to off-target activity and/or toxicity. Validation of target and its active conformation in space can be supported by antibody technology to increase relevance of hit identification in the screening step. Second, faster iterative “Design, Make, Test, Analyze” cycle can be achieved by focusing on the most fruitful hypothesis – which is a trade-off between originality of the design and complexity of the chemical synthesis. Computational chemistry solutions are expected to support medicinal chemistry teams to decide best design to work on. Integration of artificial intelligence is also expected to support the enhancement of the physiological profile, as well as the retrosynthesis strategies. Finally, early recognition of the drug candidate is needed to limit the number of compounds that are developed by medicinal chemistry AFTER the right one has been synthesized and tested. Early decision making for the drug candidate is a true challenge but will ultimately save time and resources.


Using early safety and toxicology information to increase late-stage success rate

“Failing early” in the drug development process has never helped create a new drug for patients! Even if the strategy to “fail fast” decreases costs and has been used to convince drug developers to assess early drug safety and toxicity, it loses sight of the true objective - to increase the rate of success in later stages of selected drug candidates. Indeed, identification of a safe compound is different than “deselecting” unsafe molecules. Identifying the right compounds from the beginning of drug development can rely on multiple sources of information on safety and toxicity. Safety related to a novel drug target is the earliest stage to consider. What happens when this new target is actually targeted? Metabolomics for instance can offer ways to identify and understand all related cell-mechanisms that are impacted and can lead to toxicity downstream. The use of chemical series without inherent safety issues during screening and identification of specific toxicity of lead compounds are also important to consider. No major technical barrier exists to the introduction of high throughput assays at early stages to identify organ-toxicity induced by specific compounds or chemical fragments. Additionally, new in vitro models are becoming more relevant with the advent of microfluidic technologies, co-culture and 3D cell cultures. Safety and toxicity (as well as efficacy!) are better predicted with such technologies than classic 2D cell monocultures. Some pharma companies are already developing, integrating, and using them in routine to test cardiovascular, liver or kidney toxicity. Safety remains the first reason for drug attrition in pharmaceutical development at both preclinical and clinical stages. Even if toxicity of a therapeutic strategy can be linked to the individual patient (lifestyle, age, comorbidities, etc.), the increased use of toxicity and safety assessment in early phases of drug development, provides the most informed decision for a drug candidate before preclinical testing.


Increasing portfolio opportunities with open innovation

Open innovation and collaboration is a big trend in drug discovery and development. Drug companies have different approaches to the type and extent of resources dedicated to open innovation, but all pursue the same goal - identify and align external innovations with their internal strategy. Providing access to compounds or libraries of molecules is a form of open innovation where external innovators test non-commercial chemical libraries on their own target and may identify new hits. If results are promising and both parties are interested to go further, business discussions can then be pursued. Access to technological capabilities can also be offered to external innovators. In such case the return on investment for the drug industry is knowledge. External innovators, in particular academic researchers, have a comprehensive knowledge and understanding of their topic of interest. Strategic partnerships or specific “open innovation” grants build trusts between partners and facilitate the industry’s access to knowledge. Of course, open innovation costs the pharmaceutical industry by lowering their control over confidentiality, business and IP opportunities, and innovation strategy. Adopting such collaborative behavior is not easy for pharmaceutical companies but seems necessary to keep the pace of innovation high in such a competitive and evolving environment. Moreover, recent experiences in open innovation show that it works! While the process is slower than classic internal innovation, it allows the integration of novel projects that would not otherwise be in the portfolio.


Romain Labas, Ph. D.
Partner, Senior consultant