AI Drug Discovery

UBS Wealth Management says artificial intelligence is moving beyond text generation into scientific research, opening investment opportunities across AI infrastructure, pharmaceuticals, nuclear fusion, industrial materials and utilities. The shift was highlighted by OpenAI's recent mathematical proof related to the Navier-Stokes equations, a centuries-old fluid dynamics problem and one of seven Millennium Prize Problems, which OpenAI tackled using 10,000 autonomous AI agents working in parallel for 88 hours before formalizing the proof with Lean, a system for machine-checked mathematical validation. In pharmaceuticals, multi-agent AI systems can simulate millions of protein variations in the cloud, and more than 170 AI-designed programs are already in development or clinical evaluation, including Phase III trials. In nuclear fusion, reinforcement-learning systems can predict plasma disruptions around 200 milliseconds before they occur and adjust magnetic coils thousands of times per second, while AI models in materials science can test millions of elemental combinations daily in search of properties for lighter, higher-density batteries, lower-heat computing hardware and potential room-temperature superconductors. The broader investment case centers on AI becoming a tool for automating scientific research rather than simply generating content, with companies exposed to AI infrastructure, pharmaceuticals, industrial materials and utilities positioned to benefit as these technologies move toward commercial applications.

NAVER D2SF, NAVER's in-house corporate venture arm, has invested in Silicon Valley precision medicine company ImpriMed, joining ImpriMed's $10 million Series A2 bridge round. The round was led by LB Investment, with participation from new investors NAVER D2SF, Samsung Securities, and Alois Ventures, plus follow-on investments from existing investors BonAngels and Han River Partners; it follows ImpriMed's $23 million Series A in 2023. ImpriMed combines ex vivo analysis of patient-derived live cancer cells with genomic, immunophenotypic, and clinical data through its xCellSense platform, and is developing AI models trained on more than 3.5 million data points. The company is preparing to commercialize products for blood cancers and blood infection, targeting FDA clearance and CLIA certification by Q1 2027 for an initial U.S. launch, while in South Korea its multiple myeloma prognosis and therapy-response software has been designated an Innovative Medical Device by the Ministry of Food and Drug Safety. ImpriMed was co-founded by CEO Sungwon Lim and CTO Jamin Koo, and its human healthcare expansion is supported by veterinary precision oncology work covering more than 27,000 tests for canine and feline lymphoma, used by over 600 veterinary hospitals across the United States, Canada, the United Kingdom, France, and South Korea.

Novo Nordisk is expanding its artificial intelligence capabilities through a new collaboration with Anthropic aimed at accelerating drug discovery and the development of new medicines. Under the agreement, Novo will use Anthropic's models and Claude Science across selected research and development workflows, while also applying Anthropic's frontier models to strengthen AI-driven software development. The collaboration will focus on drug discovery challenges identified by Novo's scientists and computational teams, with Claude Science initially tested in selected R&D applications involving biological reasoning. The deal adds to Novo's growing network of technology partnerships, following a strategic partnership with OpenAI in April 2026 and an August partnership with Amazon Web Services, which was named its preferred cloud provider and strategic AI partner and included a London co-innovation hub focused on drug discovery. Novo shares have lost 18% year to date against the industry's 10.9% growth, and the company currently carries a Zacks Rank #3 (Hold).

Big Picture Bio Ltd. has been founded in London to identify, design and optimise promising cancer combination therapies using a generative world model of how tumours, immune cells and surrounding tissue interact across disease sites and patient subgroups. The company has closed a £1.5 million, or roughly $2 million USD, pre-seed funding round co-led by Kadmos Capital and Exceptional Ventures, with participation from Gloucester Ventures and angel investor John White. That pre-seed round is in addition to £700,000, or roughly $950,000 USD, in non-dilutive funding from Innovate UK through its Investor Partnerships Programme, bringing total funding to £2.2 million, or roughly $3 million USD, to take its first designed drug combinations from in silico design into wet lab validation. Big Picture Bio was founded by Dr Kerstin Papenfuss, CEO and co-founder, and Dr Mark Hammond, CTO and co-founder, both veterans of Deep Science Ventures, and is advised by Dr Laura Rosenberg and Dr Duncan Young of AstraZeneca, Dr Garry Pairaudeau of DaltonTx and former CTO of Exscientia, and Dr Christian Dillon of PhoreMost. The company said its platform has been validated against real-world clinical outcomes presented at ASCO and correctly predicted the failure of Regeneron's recent fianlimab trial.

Twist Bioscience announced on 16 September 2026 an agreement with Lilly TuneLab under which Twist will provide antibody characterization data services using preferred Twist protocols to generate high-quality wet lab data that feed Lilly's AI/ML drug discovery models. The collaboration plugs Twist's DNA and antibody capabilities into Lilly's AI-driven discovery ecosystem, potentially deepening its role in data-rich, AI-enhanced antibody development workflows across the biopharma industry. The deal follows Twist's US$300,000,000 follow-on equity raise in August 2026, a pairing that highlights a company still funding growth externally while positioning itself as a preferred data and DNA supplier to big pharma and AI drug discovery partners. Twist's narrative projects $753.3 million in revenue and $127.9 million in earnings by 2029, yielding a $105.30 fair value, a 26% downside to its current price, while some of the most optimistic analysts already expected revenue of about US$715,300,000 and earnings of roughly US$128,500,000 by 2029. The agreement may reinforce that bullish view on AI-driven demand, though it does not by itself resolve the near-term issue of achieving a credible path toward breakeven or reduce dependence on a concentrated set of large NGS customers.

Alphabet's 2026 earnings-per-share estimate has climbed from $14.23 ninety days ago to $20.60 today, one of the sharpest upward revisions in mega-cap tech, as the company's AI story finally shows up in the numbers. Google Cloud grew 82% in the second quarter, Gemini Enterprise is deployed at nearly 90% of the Fortune 100, and CEO Sundar Pichai told investors Alphabet is still in a supply constraint environment. The stock has risen 42.62% over the past year and 9.36% year to date, recently brushing a 52-week high of $403.96, while the Street's consensus 12-month target sits at $422.34 with 13 strong buys, 44 buys, and just 5 holds. Analysts see revenue reaching roughly $613 billion in 2027 against $498 billion this year, and Alphabet has beaten consensus in 11 consecutive quarters while posting 12 straight quarters of double-digit revenue growth. The bull case rests on converting a $514 billion cloud backlog, with management guiding to recognize just over 50% as revenue in the next 24 months, plus TPU systems revenue that Pichai said will be largely realized in 2027, Gemini monetization across 950 million monthly active app users and more than 1 billion AI Mode users, and optionality from Waymo's 500,000-plus weekly autonomous rides and Isomorphic Labs' $2 billion raise. Risks include negative second-quarter free cash flow of $5.86 billion after $44.92 billion of capital expenditure, long-term debt of $98.2 billion, and 2026 capital spending guided at $175 billion to $185 billion.

Ginkgo Bioworks announced that its Ginkgo Datapoints offering has entered a new agreement with Lilly TuneLab, the collaborative AI/ML drug discovery platform created by Eli Lilly and Company. Under the deal, Ginkgo Datapoints will provide discovery data generation services, including small molecule developability (ADME) and antibody developability testing, to companies participating in TuneLab. John Androsavich, General Manager at Ginkgo Datapoints, said the combination of Ginkgo's automation and TuneLab's collaboration platform aims to accelerate next-generation therapeutic development across the industry, letting participants close the loop between digital design and biological reality faster than ever before. Ginkgo said its antibody and small molecule developability screening can turn around results in ML-ready formats that plug directly into TuneLab's predictive models, closing the loop between an AI-generated hypothesis and validated lab data in days rather than months. The standardized assay protocols are expected to help AI/ML models learn more efficiently, and new TuneLab members can now submit Datapoints-generated data to access additional platform model benefits. Lilly TuneLab is part of Lilly Catalyze360, alongside Lilly Ventures, Lilly Gateway Labs, and Lilly ExploR&D.

ByteDance has completed a $290 million fundraising round for its AI drug discovery unit that was spun off from the group, two people familiar with the matter said on the 16th. Shanghai-based Anew Labs reached a $1.5 billion valuation with its first external funding round. According to the sources, the round was led by HSG, IDG Capital, and Hillhouse Investment, with 5Y Capital as a co-lead investor. ByteDance and the investors declined to comment. The company said it spun off the unit because AI drug discovery is an industry different from the group's core business, and separating it would better support its long-term development; after the fundraising, ByteDance will continue to hold a 56 percent stake.

Tempus AI announced an initiative to build a research platform containing 100,000 whole genomes linked to longitudinal clinical information over the next several years, with a long-term goal of reaching one million genomes. The company said the effort will create the first de-identified multimodal whole-genome sequencing dataset built around disease populations and patient outcomes and specifically optimized for AI-driven research. The new dataset will be integrated into Tempus' existing de-identified multimodal data environment, where researchers can access genomic information alongside clinical histories, imaging, pathology and patient outcomes, and analyze it through Tempus Lens without moving datasets between systems. Development is already underway and the initial dataset is available through Tempus' Early Adopter Program, with additional members onboarded in waves and general availability planned for mid-2027. Founder and CEO Eric Lefkofsky said adding whole genome data linked to longitudinal outcomes gives researchers a richer foundation to build AI models and ultimately improve patient care.

Insilico Medicine has dosed the first patient with Rentosertib, also known as ISM001-055 or INS018_055, in GENESIS-IPF-3, the world's first Phase III clinical trial of a generative AI-driven innovative drug, at Peking Union Medical College Hospital, with Shanghai Pulmonary Hospital enrolling its first patient the same day. The 52-week prospective, multi-center, randomized, double-blind, placebo-controlled, parallel-group study is expected to enroll a total of 320 participants across 47 centers in China, with a primary endpoint of the annual rate of decline in forced vital capacity and a key secondary endpoint of time to first occurrence of any disease progression event. The trial is led by Professor Zuojun Xu of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences as Leading Principal Investigator, with Academician Nanshan Zhong of the Chinese Academy of Engineering and President Chang Chen of Shanghai Pulmonary Hospital as Co-Leading Principal Investigators. Insilico recently reported total revenue of approximately $106 million in the first half of 2026, a 287% year-over-year increase, and its first profitable half-year since listing, with an adjusted net profit exceeding $51 million, while the total contract value of transactions announced in 2026 reached approximately $7.3 billion, pushing the cumulative contract value of its major collaborations since 2021 to approximately $11 billion. Rentosertib, a potentially first-in-class small molecule targeting TNIK, received Orphan Drug Designation from the U.S. Food and Drug Administration for IPF in February 2023 and remains investigational, having not been approved by any regulatory authority.

Verily Health Inc. has received new investment support from NVIDIA, as the company extends its March fundraising, with existing investor CU Healthcare Innovation Fund II, LP also making an additional investment. The funding will support Verily's precision health AI strategy, including scaling adoption of its Verily Pre Platform and growing its patient engagement offering, Verily Me. Verily and NVIDIA previously announced a collaboration in October 2025, and researchers using the Verily Pre Platform will be able to leverage NVIDIA AI libraries and frameworks, including NeMo, Parabricks, RAPIDS, and NVIDIA B200 GPUs. Verily developed Forecast 1.0™, a foundation model integrating genomics and EHR data, in collaboration with NVIDIA, achieving improved predictive performance and computational efficiency. Stephen Gillett, Chairman and CEO of Verily, welcomed NVIDIA as a new investor, noting the investments strengthen the company's ability to build a trusted foundation for healthcare.

UpDoc, a clinical AI company, has been selected by ARPA-H to lead the ADVOCATE program, with an award of up to $9.2 million, and will be supported by Microsoft, OpenAI, and NVIDIA. The program aims to develop a first-of-its-kind autonomous clinical AI system for cardiovascular care, intended for FDA authorization and real-world deployment. Cardiovascular disease costs the U.S. over $400 billion annually, and the system will manage heart failure by handling medications, diet, and exercise. The 39-month, multi-phase effort includes milestone evaluations, independent verification, and clinical trials under an FDA Investigational Device Exemption. UpDoc's platform is already deployed at Cleveland Clinic, Allegheny Health Network, and UCSF Health.

PostEra, a Boston-based biotechnology company using artificial intelligence for drug discovery, announced that EMD Serono, Inc., the U.S. and Canada healthcare business of Merck KGaA, Darmstadt, Germany, has acquired two of its fertility programs. The programs involve novel small-molecule agonists targeting the Follicle-Stimulating Hormone Receptor (FSHR) for ovarian stimulation in IVF and the Luteinizing Hormone/Choriogonadotropin Receptor (LHCGR) for male infertility and ovulation trigger. PostEra developed these candidates using its AI platform, Proton, over the past two years, aiming to offer oral alternatives to injectable fertility treatments. EMD Serono will take sole responsibility for worldwide development and potential commercialization, though both programs are still in preclinical stages. PostEra's CEO and Chief Scientific Officer expressed confidence that the deal validates their platform's ability to tackle challenging targets and could transform IVF protocols from injections to an all-oral regimen.

Arm Holdings CEO Rene Haas said artificial intelligence could help find a cure for cancer within our lifetime, but warned that chip shortages are limiting the expansion of AI infrastructure. In an interview with the BBC, Haas said AI could eventually solve complex problems in cancer research and accelerate drug development, though modelling cells and DNA markers remains too complex today. The computing requirements for AI-driven drug discovery are already substantial, with Generate Biomedicines co-founder Gevorg Grigoryan noting that large-scale model training needs access to many GPUs, plus proprietary biological data. Bristol Myers Squibb has deployed a new NVIDIA AI computing system to support research across cancer and other therapeutic areas. Haas described the industry as in an "absolutely supply-constrained environment," saying more chip factories are needed to support growing data centers, but manufacturing capacity cannot be added overnight. He also said Arm's power-efficient technology is used in about half of AI data centers worldwide, and demand for Arm's AGI chip, developed with Meta Platforms, has exceeded $2 billion since its launch.

IQVIA announced the launch of IQVIA Predictive Clinical Development, an AI-powered approach designed to help life sciences sponsors reduce avoidable delays and bring new therapies to patients up to two years faster. The company reports measurable efficiencies including 33% faster study startup, 1.7 times more patients recruited from AI-prioritized and Prime & Partner sites with 42% higher enrollment rates, 50% faster data cleaning, and a 45% or greater reduction in time between trial phases. The platform pairs IQVIA's proprietary data and Healthcare-grade AI with technologies from Anthropic, Amazon Web Services, Databricks, Microsoft, NVIDIA, Palantir, and Snowflake to orchestrate agentic workflows. Richard Staub, president of Research and Development Solutions at IQVIA, said the offering represents a fundamental shift in making development faster, more predictable, and of higher quality. IQVIA Predictive Clinical Development includes components such as Clinical Design & Planning Suite, Push Button Start-Up, and Real-time Data Cleaning, with plans to expand across the entire development lifecycle.

AI company Owkin has signed a licensing deal with Germany's Boehringer Ingelheim, giving the drugmaker access to its AI research platform and patient data to speed up drug discovery for cancer and immunity-related diseases. The deal builds on a pilot project in 2025, where Owkin used patient tumor samples and biological datasets to help Boehringer prioritize drug targets, according to CEO Thomas Clozel. Under the new pact, Owkin will license multimodal oncology data to Boehringer and generate new data in immunology. Financial terms were not disclosed. This adds Boehringer to a growing list of drugmakers using Owkin's AI technology, K Pro, which AstraZeneca licensed in May and Sanofi expanded with a five-year agreement in June.

OmniAb, Inc. has announced a global collaboration and license agreement with Eli Lilly and Company to discover and develop novel ion channel therapeutics, granting Lilly exclusive global commercialization rights in exchange for an upfront payment, up to $370 million in development and commercial milestones, and tiered sales royalties. The deal leverages OmniAb's specialized antibody discovery platform, though the specific therapeutic target remains undisclosed. Financially, Eli Lilly reported Q2 2026 revenue of $23 billion, up 48% year-over-year, with non-GAAP earnings of $8.38 per share, and raised its full-year revenue guidance to $85.0–$87.0 billion. OmniAb, in contrast, reported Q2 2026 revenue of $13.4 million, up from $3.9 million a year earlier, narrowed its net loss to $5.9 million, and raised its full-year revenue guidance to $32–$36 million. The partnership pairs a micro-cap discovery engine with a pharmaceutical titan, and investors should watch OmniAb's cash burn and the progression of its 34 clinical-stage partner programs, as well as Lilly's execution on its raised guidance and supply chain expansions.

BenchSci announced a strategic, multi-year initiative establishing Google Cloud as the primary infrastructure platform for EMET, its agentic research environment for preclinical drug discovery. The combined solution gives pharmaceutical scientists unified access to BenchSci's proprietary biological knowledge graph—858 million nodes, 2.2 billion relationship edges, and legal access to 16 million closed-access scientific papers—alongside Google's frontier life sciences AI models, including AlphaGenome and AlphaFold 3, within a single environment. BenchSci reports that 70% of drugs fail in the clinic due to fragmented data, and scientists spend half their time manually integrating disparate sources. The majority of the top 20 pharmaceutical companies by revenue are existing BenchSci customers, with 80% of users reporting 60% efficiency gains and some teams achieving up to 50x time savings. BenchSci is also working to integrate EMET into the Google Cloud Marketplace for simplified access and billing.

The Ministry of Health, Labour and Welfare announced on the 26th its budget request for fiscal 2027, with a total general account of 36.58 trillion yen, up 4.4% from the initial budget for fiscal 2026, marking a record high. The increase is driven by rising social security costs due to an aging population. The ministry is prioritizing the strengthening of drug discovery and advanced medical care, and will begin supporting companies that develop innovative new drugs. Wage increases for care workers are listed as a "matter request" without specifying amounts, with the intention to finalize details during the budget formulation process at the end of the year.

Chengdu HitGen released its 2026 interim report on August 26. During the reporting period, the company achieved operating revenue of 346 million yuan, up 52.41 percent year on year. Net profit attributable to the parent company was 80.68 million yuan, up 61.21 percent. Net profit after deducting non-recurring items was 76.98 million yuan, up 42.80 percent. The performance growth was mainly driven by a recovery in global demand for innovative drug research and development and strong growth across business segments. The DEL business, as the cornerstone, recorded revenue of 166 million yuan, up 62.14 percent year on year, with gross margin maintained at 77.43 percent. The OBT segment posted revenue of 54.03 million yuan, a sharp increase of 94.03 percent. The FBDD and SBDD segment led by the UK subsidiary Vernalis recorded revenue of 85.09 million yuan, up 30.43 percent. In addition, Motian Intelligence, which was consolidated as a controlling stake at the end of 2025, contributed data service revenue of 15.44 million yuan, becoming a new growth driver. The company's net cash flow from operating activities was 121 million yuan, up 9.44 percent year on year. However, affected by the appreciation of the renminbi, the company incurred exchange losses of about 14.17 million yuan during the period. Looking ahead, the company faces exchange rate fluctuation risks and goodwill impairment pressure, and needs to monitor the order conversion efficiency of the DEL and OBT segments as well as the clinical progress of proprietary pipeline projects such as HG146.

Chengdu HitGen released its 2026 half-year report. First-half net profit attributable to the parent was 80.68 million yuan, up 61.2% year on year. Operating revenue was 346 million yuan, up 52.4% year on year. Net profit attributable to the parent after deducting non-recurring items was 76.98 million yuan, up 42.8% year on year. Net operating cash flow was 121 million yuan, up 9.4% year on year. Earnings per share were 0.2013 yuan. In the second quarter, operating revenue was 185 million yuan, up 54.2% year on year, and net profit attributable to the parent was 39.18 million yuan, up 80.1% year on year. As of the end of the second quarter, total assets were 1.995 billion yuan, up 2.1% from the end of the previous year, and net assets attributable to the parent were 1.526 billion yuan, up 1.6%. During the reporting period, all business segments achieved growth. DEL business revenue was 166 million yuan, up 62.14% year on year. FBDD and SBDD platform revenue was 85.09 million yuan, up 30.43% year on year. OBT segment revenue was 54.03 million yuan, up 94.03% year on year. TPD segment revenue was 8.46 million yuan, up 12.25% year on year.

Bristol Myers Squibb announced a new collaboration with Chai Discovery to advance AI-driven therapeutic antibody discovery. The agreement focuses on using artificial intelligence and machine learning to support the identification of novel therapeutic antibody candidates. The move reflects Bristol Myers Squibb's effort to integrate advanced computational tools into its drug discovery work. Investors should watch for pipeline updates where the company attributes new antibody programs or faster candidate selection to this AI system.

Biotech stocks reached their highest level since the height of the pandemic after Moderna and Merck announced that a late-stage trial testing their messenger RNA-based cancer therapy met its main goals. Healthcare became the best-performing sector in the S&P 500, with the State Street SPDR S&P Biotech ETF adding more than 4% to reach its highest level since February 2021. The individualized neoantigen therapy intismeran autogene, combined with Merck's Keytruda, improved recurrence-free survival with a statistically significant and clinically meaningful effect in the Phase 3 INTerpath-001 trial. Moderna shares more than doubled, Merck added over 12%, and rival vaccine makers BioNTech and Novavax also gained sharply. Gene editing companies including Prime Medicine, Intellia, CRISPR, Editas Medicine, and Beam Therapeutics were notable gainers, while AI-related biotechs Absci and Recursion Pharmaceuticals rallied after Anthropic selected Twist Bioscience as an independent evaluator.

Guolian An Fund released investment views, believing that the high prosperity of the pharmaceutical industry has been confirmed, and the AI drug discovery sector has opened up room for imagination. Last week, the pharmaceutical sector was generally stable but internally divergent. Stocks related to scientific research services and AI drug discovery continued to be strong, with multiple stocks rising more than 20% in a single week. The retail pharmacy sector performed prominently in the first half of the week, while innovative drug blue chips were relatively under pressure. Orders in the wet-lab segment of AI drug discovery are accelerating toward realization. A protein synthesis leader disclosed in its interim report that AIDD service revenue in the first half of 2026 approached 40 million US dollars, with a year-on-year growth rate exceeding 105%, and full-year revenue is expected to surpass 100 million US dollars. A second-tier manufacturer's AIDD business revenue in the first half of the year has already reached twice its full-year 2025 level. The strength in retail pharmacies stemmed from improved same-store sales in July, the clearing out of small and medium-sized chains, customer flow concentrating toward leading players, and a high incidence of respiratory diseases. Guolian An cautioned that some stocks are already valued based on 2028 and 2029 earnings, and volatility may rise. It suggested that investors use pharmaceutical ETFs or off-exchange index funds to capture the industry's upward prosperity, and pointed out that the CSI Pharmaceutical 100 Index has a trailing-twelve-month price-to-earnings ratio of 34.35 times, at the 54th percentile of the past ten years, indicating that valuations still have room for repair.

OmniAb Inc. shares soared almost 18% in premarket trade after the company raised its cash forecast for 2026 on the back of recent license and business-development agreements. The business now intends to complete the year with $49 million to $53 million in cash and cash equivalents, compared with a prior estimate of $37 million to $41 million. The upgrade comes on the back of recent licensing activities in technology including a contract with Eli Lilly in relation to the company's ion-channel program. Seeking Alpha has previously claimed that the Lilly license deal might be worth $370 million. For a smaller biotech outfit, the capital injection is crucial as it buys management some breathing room on funding operations without needing to tap the equity markets right away.

Flexsteel Industries reported fourth quarter 2026 results with revenue growth of 27.3%, driven by a structural shift in customer demand toward AI-driven drug discovery and high-throughput protein expression. Management attributed record adjusted net profit growth of over 200% to improved business quality and operating leverage from long-term investments in automation and digital capacity. The Life Science Group achieved a 29.5% adjusted operating margin, marking a transition from an investment phase to a scale-and-profitability phase. Full-year revenue growth guidance for the Life Science segment was raised to 25%-30%, reflecting strong visibility into AIDD-related order momentum. AIDD orders are projected to double in the second half of 2026, with management expecting this hyper-growth trajectory to compound over the next several years. The company expects to achieve positive EBITDA for the ProBio CDMO segment by 2027, supported by a 54% year-over-year increase in new orders. CapEx for 2026 is projected at approximately USD 130 million, focused on doubling throughput capacity every quarter to meet surging AI-driven validation demand. Management assumes that the premium margins for AIDD services, roughly 20 points higher than traditional protein orders, will remain sustainable due to the high value of model-ready data. Prior period figures were adjusted to exclude the financial impact of the Renova license transaction to provide a more objective view of underlying performance. Management identified the primary industry bottleneck as the validation of AI-generated designs, which traditional experimental workflows are not equipped to handle at scale. The company maintains a robust cash position of approximately USD 830 million, stating there is no immediate need for incremental financing despite aggressive capacity expansion. Tariff refunds in the U.S. impacted gross margins, with adjusted figures provided to show the underlying operational improvement excluding these one-time effects. In the Q&A session, management noted that AIDD programs require exponentially higher throughput and continuous engagement compared to traditional discovery, and current guidance is described as prudent with potential for further upside if the trend of complex, recurring AIDD projects continues to accelerate. Management claims a clear advantage in speed and data quality, delivering binding data in 4 to 7 days compared to an industry average of over 2 weeks, and GenScript captures more than twice the revenue per delivered item versus its primary competitor by focusing on end-to-end validation rather than just DNA fragments. The company's modular workstation infrastructure allows for faster capacity expansion with lower capital intensity than large-format systems. New AI-native and tech-sector customers require validation for thousands of candidate sequences in a single iteration, necessitating a shift from months to days in feedback loops, and the deliverable for these clients is not just a biological construct but high-quality experimental data used to retrain and improve AI models. This segment is viewed as a structural long-term driver because it embeds GenScript into the customer's core R&D digital infrastructure.