The role of artificial intelligence (AI) in therapeutic design has fundamentally transitioned from an experimental instrument to a core foundation of drug research and development (R&D). Sino Biological contributes significantly to this changing landscape by serving as a vital bridge between computational prediction and experimental truth.
Image Credit: peterschreiber.media/Shutterstock.com
Current AI trends in drug development
According to a recent industry survey, around 81% of pharmaceutical companies currently employ AI in at least one development program.1 Key workflows in pharma R&D that utilize AI include predictive modeling and the identification and selection of novel therapeutic candidates (Figure 1).
This trend is driven by substantial financial commitments. Leading pharma companies, including Pfizer, Takeda, and AstraZeneca, have significantly increased their investments in AI in recent years, with a specific focus on therapeutic discovery.
Figure 1. Current AI usage in pharmaceutical R&D. Image Credit: Norstella1
The global AI-driven therapeutic discovery market was valued at roughly $3.1 billion in 2025 and is projected to reach $4 billion in 2026.2 Top AI-first biotechs include Isomorphic Labs (Alphabet), Insitro, Insilico Medicine, and Recursion.2
These key companies are utilizing proprietary systems and high-value partnerships with conventional pharmaceutical organizations to accelerate development timelines, minimize overall expenses, and increase the likelihood of successful therapeutic candidates.
As an example, Isomorphic Labs signed AI-based therapeutic discovery deals worth almost $3 billion with pharmaceutical giants Eli Lilly and Novartis, while another AI startup, Chai Discovery, announced a collaboration with Eli Lilly to accelerate therapeutic discovery through generative design models.3,4
The role of high-throughput expression in AI design
The continuous advancement of AI models for de novo design has increased the demand for rapid wet lab verification.5,6 Sino Biological’s high-throughput (HTP) antibody generation platforms based on dual-expression systems - mammalian and cell-free systems - have emerged as pivotal tools that can rapidly produce thousands of AI-designed antibody variants.
This allows scientists to move smoothly from AI-generated sequences to functional antibodies within days, supporting the rapid design-build-test-learn cycles needed to refine AI models (Figure 2).
Figure 2. General workflow of AI-driven drug discovery. Image Credit: Sino Biological Inc.
Proven mammalian excellence and rapid cell-free innovation
Conventional mammalian expression systems, including HEK293 and CHO cell lines, continue to be the industry gold standard for HTP generation of recombinant antibodies, including full-length IgG, VHH, and scFv.
Sino Biological leverages its deep expertise in HTP gene synthesis, vector construction, and optimized transient antibody expression technology to generate small-scale, high-quality recombinant antibodies, providing industry-leading throughput (10,000+ antibodies/month) and speed (10 days from gene to antibody).
In addition, direct access to a catalog featuring more than 10,000 premium recombinant proteins enables swift, precise binding validation of these antibodies, guaranteeing specificity and high-quality data.
For projects demanding even faster turnaround times or involving proteins that are challenging to express in mammalian cells, cell-free protein synthesis (CFPS) systems offer a quick and efficient option.7
CFPS, also referred to as in vitro translation, enables the HTP generation of target proteins from DNA templates by employing the translational machinery outside of living cells (Figure 3).
This strategy bypasses the speed limitations of cell-based systems, cutting down production timelines from weeks to hours. Sino Biological completes antibody expression in just three hours using CFPS systems, matching the pace of AI-fueled discovery.
From AI-generated sequences to synthesis, expression, purification, and validation, the entire workflow is seamless, enabling the transition from in silico design to functional antibodies in a matter of days.
In addition, by eliminating cellular viability constraints, CFPS enables the synthesis of challenging or toxic proteins and the incorporation of non-natural amino acids, thereby allowing AI-fueled design to reach its full potential.
Figure 3. Cell-free protein synthesis process. Image Credit: Sino Biological Inc.
Case study of HTP scFv-His and VHH-His synthesis via CFPS
A recent project featuring more than 2000 AI-designed scFv and VHH sequences showcased the HTP capacity of Sino Biological’s CFPS platform (Figure 4). The entire library underwent parallel synthesis and expression, followed by binding affinity evaluation using BLI.
This integrated HTP workflow bridges production and characterization, supporting the efficient identification of promising leads with picomolar affinity and the generation of crucial data for additional pipeline optimization.
Figure 4. Case study: HTP cell-free expression of over 2000 scFv-His and VHH-His antibodies, followed by affinity analysis via BLI. Image Credit: Sino Biological Inc.
Derisking antibody discovery through early developability assessment
Early-stage developability profiling is vital for derisking the therapeutic discovery pipeline and refining candidate selection.8,9 A thorough antibody developability analysis enables the proactive identification and management of potential challenges, such as screening out candidates that exhibit good binding properties but possess unwanted biophysical characteristics.
To expedite candidate triaging and early-stage optimization, Sino Biological offers an integrated platform for HTP antibody developability assessment, featuring about 20 ready-to-use assays that evaluate critical properties including homogeneity, stability, solubility, and specificity. Versatile assay selection and customization are available to fulfill specific project specifications.
With this platform, comprehensive developability characteristics can be rigorously evaluated, including thermal stability (nanoDSF/DSC), hydrophobicity (HIC-HPLC/PAIA-HIC), self-association (AC-SINS), polyreactivity (BVP/DNA/Insulin ELISA), and colloidal stability (SMAC-HPLC) (see Table 1).
High-quality, structured data is delivered efficiently, supporting AI/ML model training and accelerating therapeutic discovery campaigns.
Table 1. Antibody developability assays at Sino Biological. Source: Sino Biological Inc.
| Category |
Assays |
| Purity |
SEC-HPLC/SDS-PAGE |
| Titer |
ELISA |
| Solubility |
DLS |
| Intact mass |
LC-MS |
| Colloidal stability |
SMAC-HPLC |
| Thermo stability |
nanoDSF/DSC |
| Aggregation |
SEC-HPLC/SEC-MALS |
| Self-association |
AC-SINS |
| Hydrophobicity |
HIC-HPLC/PAIA-HIC |
| Size distribution and aggregation |
DLS |
| Target binding |
ELISA/SPR/BLI |
| Affinity analysis |
FACS/SPR/BLI |
| FcγR/FcRn/C1q binding |
SPR/BLI |
| Polyreactivity |
BVP/DNA/Insulin ELISA |
| Cell-based assay |
Assay specific |
Synchronizing discovery: An Integrated HTP platform for AI-guided innovation
With the rapid progression of AI-guided innovation, matching experimental throughput to the scale of contemporary discovery is imperative. This is particularly crucial as antibody pipelines expand, driving the need for efficient HTP expression and parallelized assay workflows.
Sino Biological’s integrated antibody generation and developability assessment platform optimizes this workflow via a comprehensive HTP strategy, allowing for the analysis of thousands of antibodies within compressed timelines.
From AI-designed sequence inputs to robust, high-precision data outputs, this unified HTP platform delivers a comprehensive picture of antibody developability profiles, efficiently expediting the transition from initial discovery to sophisticated therapeutics.
References and further reading
- Norstella. (2024). AI transformation in pharma R&D | Trends & insights | Norstella. Available at: https://www.norstella.com/resource/assessing-ai-transformation-pharma-rd/.
- Global Market Insights Inc. AI in Drug Discovery Market Size & Share Forecast Report - 2032. Available at: https://www.gminsights.com/industry-analysis/ai-in-drug-discovery-market.
- Isomorphic Labs. Isomorphic Labs kicks off 2024 with two pharmaceutical collaborations - Isomorphic Labs. Available at: https://www.isomorphiclabs.com/articles/isomorphic-labs-kicks-off-2024-with-two-pharmaceutical-collaborations.
- Ropek, L. (2026). From OpenAI’s offices to a deal with Eli Lilly – how Chai Discovery became one of the flashiest names in AI drug development | TechCrunch. TechCrunch. Available at: https://techcrunch.com/2026/01/16/from-openais-offices-to-a-deal-with-eli-lilly-how-chai-discovery-became-one-of-the-flashiest-names-in-ai-drug-development/ .
- Zhu H, et al. Integration of AI and high-throughput technologies in drug discovery. Biology. 2025; 14(9): 1268. https://doi.org/10.3390/biology14091268
- Li X, et al. Advanced drug delivery systems and AI-driven formulation optimization. Pharmaceutics. 2023; 15(7): 1916. https://doi.org/10.3390/pharmaceutics15071916
- Wang Y, et al. Monoclonal antibody developability assessment: Challenges and opportunities. Antibodies. 2015; 4(1): 12. https://doi.org/10.3390/antib4010012
- Chen L, et al. Emerging trends in AI-powered biopharmaceutical R&D. Military Medical Research. 2025; 12: 00764-4. https://doi.org/10.1186/s40364-025-00764-4
- Nature Biomedical Engineering. Navigating the interface of AI and wet lab automation. Nat Biomed Eng. 2025; 9: 00349-8. https://doi.org/10.1038/s44222-025-00349-8
About Sino Biological Inc.
Sino Biological is an international reagent supplier and service provider. The company specializes in recombinant protein production and antibody development. All of Sino Biological's products are independently developed and produced, including recombinant proteins, antibodies, and cDNA clones. Sino Biological is the researchers' one-stop technical services shop for the advanced technology platforms they need to make advancements. In addition, Sino Biological offers pharmaceutical companies and biotechnology firms pre-clinical production technology services for hundreds of monoclonal antibody drug candidates.
Sino Biological's core business
Sino Biological is committed to providing high-quality recombinant protein and antibody reagents and to being a one-stop technical services shop for life science researchers around the world. All of our products are independently developed and produced. In addition, we offer pharmaceutical companies and biotechnology firms pre-clinical production technology services for hundreds of monoclonal antibody drug candidates. Our product quality control indicators meet rigorous requirements for clinical use samples. It takes only a few weeks for us to produce 1 to 30 grams of purified monoclonal antibody from gene sequencing.
Sponsored Content Policy: News-Medical.net publishes articles and related content that may be derived from sources where we have existing commercial relationships, provided such content adds value to the core editorial ethos of News-Medical.net, which is to educate and inform site visitors interested in medical research, science, medical devices, and treatments.