Eight companies rewriting biology.

Insitro builds a data-driven drug discovery platform using induced pluripotent stem cells at scale and machine learning models trained on large phenotypic datasets to identify novel targets and predict clinical outcomes. Galdera invested at Series A in 2019, convinced by the depth of the biological data generation system and the founding team's bench-science credibility.

Asimov applies synthetic biology and computational design to engineer mammalian cells with precision, enabling the creation of more effective and predictable cell-based therapies and biologics. The platform's ability to specify genetic circuits and predict expression behavior represented the kind of computational engineering rigor we look for.

Recursion industrializes drug discovery by running millions of experiments and applying machine learning to map the relationships between biological perturbations and cellular phenotypes at scale. Galdera's 2018 Series A investment was one of the firm's earliest positions, made when Recursion's phenotypic screening platform was generating disease-area insights unattainable by traditional target-centric approaches.

Kymera uses its Pegasus platform to rationally design protein degraders — small molecules that co-opt the cell's natural protein disposal system to selectively eliminate disease-causing proteins. Targeted protein degradation offers access to targets previously considered undruggable; Galdera invested at Series A in 2018, ahead of the field's broader recognition of the mechanism's potential.

Cellarity treats the cell, not the target — using single-cell genomics and machine learning to understand how disease manifests at the level of cellular state, and designing interventions that restore healthy cell function rather than blocking individual proteins. The system-level approach to cellular disease aligned with Galdera's thesis on platforms that exceed single-target drug discovery.

Exscientia uses AI-driven design to produce optimized small-molecule drug candidates at a fraction of the time and cost of traditional medicinal chemistry programs. Their early demonstration of AI-designed molecules reaching clinical trials in candidate-nomination timelines measured in months validated the platform's generalizability across target classes.

Strand designs mRNA circuits — genetic programs encoded in mRNA that can sense signals inside cells and execute therapeutic responses conditionally, enabling precision control of where and when a therapy is active. The computational approach to RNA circuit design represented a convergence of synthetic biology and programmable therapeutics that Galdera had been tracking since Fund I.

Cerebras Bio is building computational infrastructure specifically architected for biological simulation workloads — enabling large-scale molecular dynamics and protein-protein interaction simulations that are impractical on general-purpose compute. Infrastructure that reduces the computational cost of biology improves the economics for every discovery-platform company in the portfolio.