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Antibodies
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“We know AI can accelerate many steps in drug development… but we have to take every
one of these generative medicines and run them through testing, early preclinical testing, clinical
testing in humans.”
— Vas Narasimhan, CEO, Novartis
“Generative models can’t be trusted without validation… Experimental button-main mt-3 is more
important
than speed, reach or access to compute.”
— Alex Zhavoronkov, PhD, Founder & CEO, Insilico
Medicine
Select your target modality
Antibodies
Nanobodies (VHH)
De Novo Proteins & Protein Binders
Enzymes
AI is revolutionizing antibody engineering by precisely designing CDR loops, optimizing affinity, and enhancing developability for complex therapeutic targets.
Recommended Platforms:
With their simple, stable structure, VHHs are ideal targets for AI-driven de novo design, enabling rapid screening cycles for your computational libraries.
Recommended Platforms:
AI-driven de novo protein unlocks therapeutic potential by creating novel protein scaffolds and mini-binders precisely engineered to engage difficult drug targets.
Recommended Platforms:
AI-powered enzyme engineering, whether through de novo design or directed evolution, requires rapid, high-throughput validation of catalytic activity and stability.
Recommended Platforms:
| Response | Result |
|---|---|
| >0.10 | Positive |
| 0.03~0.10 | Ambiguous |
| <0.03 | Negative |
DSF
| Protein name | Conc. (mg/mL) | Avg Tm1 (℃) | Avg Tm2 (℃) | Avg Tonset (℃) | Avg Tagg (℃) |
|---|---|---|---|---|---|
| SG- 201.1B4-M001 | 2.28 | 72.35 | 83.26 | 65.91 | 64.31 |
DSF
| Protein name | Conc. (mg/mL) | Temp (℃) | Z-Ave. Dia. (nm) | PDI | Fit Var. | Pk 1 Peak Dia. (nm) | Pk 1 Mass (%) | Pk 2 Peak Dia. (nm) | Pk 2 Mass (%) |
|---|---|---|---|---|---|---|---|---|---|
| SG-201.1B4-M001 | 2.28 | 25.02 | 18.65 | 0.252 | 0.012 | 11.27 | 99.83 | 109.53 | 0.17 |
| 24.97 | 19.49 | 0.212 | 0.032 | 10.45 | 99.89 | 125.05 | 0.11 |
HIC HPLC
MAbPac™ HIC-10 HPLC Column
AC-ICIEF
BVP assay
BVP ELISA (Baculovirus Particle ELISA) is an in vitro binding assay that detects the nonspecific or polyspecific binding of antibodies to complex biological surfaces, using inactivated baculovirus particles as a surrogate for “self” or “off-target” antigens.
FcRn binding assay
One of the key mechanisms controlling an antibody's PK clearance is its pH-dependent binding to the FcRn receptor. The FcRn Binding Assay is used to measure this specific interaction, providing a reliable prediction of an antibody's in vivo half-life.
AI Companies Served
AI-Designed Proteins Expressed
Model-Ready Data Points Generated
Industrial-Scale Automation
Leverages GenScript’s world-class CRO capacity for unparalleled speed and scale. We process 1,000+ samples daily, delivering 2-3x more screening per budget. Get your results in 1 week.
Seamless Model-Ready Data
Our platform delivers model-ready, structured data directly to your pipeline via a secure API. Faster, safer, and ready to train your AI engine.
Comprehensive Expression Expertise
With CHO, Cell-Free, and E. coli systems under one roof, we match each AI-designed protein to its ideal host. We deliver yields of 50-400µg, which is more than sufficient for affinity screening.
Successfully help EvolutionaryScale, an AI startup screen and discover a novel version of green fluorescent protein (GFP)
This finding was featured on the cover of Science’s February issue in 2025.
Hayes, Thomas, et al. Simulating 500 Million Years of Evolution with a Language Model. Science387,850-858(2025). ; https://www.science.org/doi/10.1126/science.ads0018
The Challenge
Latent Labs needed to experimentally validate their Latent-X AI model, which designed 100 de novo mini-binders against five different therapeutic targets. They required a "build and test" partner to translate these digital designs into functional in vitro binding data at scale.
The Solution: GenScript's "Build & Test" Platform
GenScript provided an end-to-end service to bridge the in silico to in vitro gap.
The Outcome
GenScript's platform provided the core in vitro data that validated the Latent-X AI model. The results confirmed high experimental hit rates (e.g., 64% on BHRF1 ) and potent, high-affinity binders in the low-nanomolar to picomolar range, proving the model's superior performance.
Preprint: "Latent-X: An Atom-level Frontier Model for De Novo Protein Binder Design"
https://doi.org/10.48550/arXiv.2507.19375
Viiv Healthcare
Dr.
Tiancen Hu
Scientific Director
The TurboCHO™ system of GenScript has dramatically accelerated the engineering
and optimization of our biologics programs including multispecific modalities.
The throughput, quality and turnaround time are top notch in industry, routinely
providing us hundreds of purified bispecific antibodies with high purity, low
endotoxin, high yield (enough for both functional and mouse PK study from 20 ml
culture!) and even normalized concentration. All these can happen within a few
weeks after we submit the sequences. To us, this is a game changer especially in
the era of AI/ML-aided protein engineering.
Twain Therapeutics
Dr. Yuankai W.
Senior Director
Twain Therapeutics engaged GenScript to support developability assessment across our multispecific antibody portfolio. The thermal stability and purity analyses were performed to a high standard and delivered on the promised timeline. Their scientists were responsive and collaborative from study design through data review, and the final reports were clear, well‑organized, and easy to hand off to project teams. The work accelerated down‑selection and de‑risked our next experiments. We look forward to partnering with GenScript again.
