In a report published on July 16 2026, titled Lab-in-the-Loop: AI Rewires Antibody Discovery, Unlocking a US$7 billion LST Opportunity, “Lab-in-the-Loop” (LitL) is described as an emerging approach in which AI models propose candidate antibody sequences, wet lab experiments test them, and the resulting data is fed back into the AI to improve the next round of designs. This transforms what was once a slow, serial discovery process into a faster, guided one.

In the report, Leerink Partners has identified Carterra, a provider of high-throughput surface plasmon resonance (HT-SPR) platforms for antibody and small molecule discovery, as a key enabling technology in the fast-growing market for AI-driven biologics drug discovery.

Leerink Partners analyst Puneet Souda and colleagues estimate a total addressable market of roughly US$7 billion in life science tools demand tied to AI-enabled antibody discovery — including a US$4 billion biologics drug discovery layer, of which an estimated US$1.3 billion is currently outsourced to service providers.

The Leerink report concludes that this shift increases rather than diminishes the need for wet lab data and identifies binding affinity measurement, where surface plasmon resonance (SPR) instruments quantify how tightly an antibody binds its target, as a segment expected to remain central to the discovery process rather than simply benefiting from higher project volumes. Its competitive landscape analysis names Carterra, alongside other technologies, as a primary supplier of this binding affinity infrastructure.

Josh Eckman, Chief Executive Officer and Co-Founder of Carterra, said: “This report reinforces what we’re hearing directly from our customers: as AI generates larger and more complex sets of antibody candidates, the bottleneck shifts to how quickly and accurately those candidates can be validated at the bench.

“Carterra’s high-throughput SPR platforms were built for exactly this kind of scale, and we believe we’re well positioned to benefit as Lab-in-the-Loop becomes the default way biologics programs are run.”

Industry voices point to rising demand

According to Carterra, ten of its customers are named in the Leerink report and are already describing the increase in scale anticipated by the analysts.

Twist Bioscience, which the report identifies as the largest structural beneficiary of the LitL shift, has highlighted Carterra’s role in generating the antibody binding datasets that large-scale AI discovery programmes depend on. At the Protein and Antibody Engineering Summit (PEGS Boston) in May 2026, Twist Biopharma Solutions’ Chief Scientific Officer Dr Colby Souders described the role Carterra’s platforms play in its partnership with AWS Biodiscovery to generate binding data at the scale required by modern AI-guided discovery campaigns.

Julian Englert, Chief Executive Officer and Co-Founder of Adaptyv Bio, a protein engineering company supporting AI-driven biologics programmes that is also named in the report, said: “The market opportunity may be understated. AI in drug discovery is here to stay and we believe Leerink’s estimate of a ~US$4 billion antibody discovery market may be low. At Adaptyv, we are seeing massive increases in both orders for our protein synthesis but also the size of projects being requested. We have deployed the most sophisticated and high-throughput technologies, like Carterra platforms, to maintain our leadership in the space.”

Why binding data matters

The Leerink report argues that AI models are only as effective as the experimental data used to train and refine them. Each round of the Lab-in-the-Loop cycle depends on fast, accurate, high-volume binding affinity data to identify which candidates perform successfully, with that information generated through wet lab testing. The analysis notes that legacy approaches to binding characterisation, often limited to simple yes/no assays or low-throughput instruments, are increasingly being replaced by platforms designed to match the scale of candidate pools generated by AI models.