Precision Medicine meets Drug Discovery

Cantos Ventures
Published in
3 min readMay 17, 2022


Why we invested in Character Biosciences

Given what we know about the diversity and heterogeneity locked within biology, it’s surprising that most drugs are still discovered and prescribed as one-size-fits-all. The typical process involves identifying a gene or target, modifying drug chemistry to block (or activate) that target, and running preclinical/clinical studies starting with mice models and eventually progressing to human studies if all goes well. Such an abstract approach to drug discovery largely ignores the inherent differences in disease biology between and often within patient populations, especially in diseases of aging where heterogeneity is even more profound.

Until recently, we didn’t have the bandwidth to consider individual genomes and tumors when designing drugs, instead defaulting to simpler tools such as genome-wide association studies (GWAS) that may help identify genotypic variants of disease but don’t easily correspond to phenotypic outcomes. With an increasing number of tools available to understand biology — genome sequencing, proteomics, spatialomics, single-cell sequencing — there is now a need to combine various forms of patient data and discover insights that lead to more precise treatments.

Some companies are starting to make strides in precision medicine, the customization of healthcare tailored to subgroups of patients based on genotyping. For example, 23andMe is taking its broad genomics databases and starting to explore drug discovery, with a first oncology drug already in clinical trials. Others like Tempus Labs focus on aggregating multi-omics data to better understand disease manifestation.

Limitations to genome-wide association studies. Source: Nature

As we learn more about biology, it’s become apparent that most diseases are polygenic and manifest differently in distinct groups of patients. The ideal drug development and treatment process should involve a precise matching of deep genomics to phenotype; in other words, matching patient genetics to expected treatment outcomes. In order to achieve this vision, we first have to build libraries of integrated patient data and then link insights back to interventions with machine learning. It’s no small undertaking.

Character Biosciences is doing just that. Formerly known as Clover Therapeutics, Character is building an integrated precision medicine platform focused on designing treatments for diseases of aging. They have formed extensive partnerships with patients, providers, and payers to build integrated clinical genomics databases that are a goldmine of information used towards 1) designing better drugs and 2) matching the right patients to the right drugs. Character takes this data and applies advanced computational biology models to reclassify disease into molecular subtypes, build companion diagnostics that stratify patients by expected treatment response, and discover genetically-validated drug targets.

Under Character’s approach, treatments are matched to patients’ unique biology.

We first partnered with Cheng and Marcel in their seed round alongside Lifeforce Capital, Casdin Capital, and KdT Ventures back when Character was Clover Therapeutics. It’s been incredible watching Cheng and Marcel grow and build a world-class team as they tirelessly work towards the same goal — more intelligent treatments for patients. We couldn’t be more excited to work with Series A lead, our friends at Innovation Endeavors, as well as new investors Section 32 and Catalio Capital as we deepen our partnership with Character in this $18M Series A.

If you are excited by the mission to integrate precision medicine into drug discovery for age-related disease, check out open roles here.

Character’s first drugs are targeting age-related macular degeneration. If you’re a patient or provider looking to get involved with Character’s research, you can learn more here.



Cantos Ventures

A venture firm built for concept-stage startups building the near frontier.

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