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5 posts about Life Sciences. Every summary links to the original.
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BioNeMo Inference Runtime runs one pipeline per target: parse, tokenize, generate features, infer on a GPU replica, and write a structure. This diagram traces those stages and the throughput trade-off.
Antibody discovery is a three-stage prediction pipeline, and AI models that excel on familiar targets degrade sharply on unfamiliar ones. This explainer maps where that gap appears and what it costs.
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CSIRO built Serverless Beacon (sBeacon), a production-ready implementation of the Global Alliance for Genomics and Health (GA4GH) Beacon protocol for secure genomic variant querying. Its serverless architecture combines Amazon S3, AWS Lambda, Amazon DynamoDB, and Amazon Athena: genomic data remains in its original S3 location, while metadata is indexed in ORC tables and ontology indexes for query processing. Standard VCF files can be queried through API Gateway, with modular Lambda functions resolving ontology terms, querying Athena, and, when needed, issuing HTTP byte-range requests to source buckets so raw VCF bytes do not leave their owning organization. The post reports support for hundreds of millions of individuals and billions of genomic locations, approximately USD 0.40 monthly operation for a 1000 Genomes-scale dataset, roughly five-second real-world queries, and about 18-second generation-to-use onboarding, while noting that whole-genome range queries can time out.
Anthropic is launching Anthropic's AI for Science program, an initiative that provides free API credits to researchers pursuing high-impact scientific projects, with particular emphasis on biology and life sciences. Qualified researchers will be selected according to their contributions to science, the potential impact of proposed research, and whether AI can meaningfully accelerate the work. The program is intended to support uses including analyzing complex scientific and genetic data, generating hypotheses, designing experiments, communicating findings, understanding biological systems, accelerating drug discovery, and increasing agricultural productivity. Researchers attached to research institutions can apply through an application form, with reviews conducted by Anthropic's team and subject matter experts in relevant fields.
Anthropic is expanding Claude into a life sciences partner intended to support work from early discovery through translation and commercialization, beyond earlier uses for coding and paper summarization. The rollout combines model improvements, scientific connectors, Agent Skills, a prompt library, and dedicated support for researchers, clinical coordinators, and regulatory affairs managers. On Protocol QA, Sonnet 4.5 scores 0.83 against a human baseline of 0.79 and Sonnet 4’s 0.74, while BixBench shows a similar improvement over its predecessor. Connectors include Benchling, BioRender, PubMed, Scholar Gateway, Synapse.org, and 10x Genomics, while a single-cell-RNA-QC skill applies scverse best practices to quality control and filtering; use cases also cover literature reviews, protocols, bioinformatics, and regulatory submissions. The offering is available through Claude.com and the AWS Marketplace, with Google Cloud Marketplace availability described as coming soon.
Anthropic announces Claude for Healthcare and expanded Claude for Life Sciences capabilities, adding HIPAA-ready tools for providers, payers, health-tech companies, and individuals managing personal health data. Healthcare connectors cover CMS coverage determinations, ICD-10 codes, the National Provider Identifier Registry, PubMed, and beta integrations with HealthEx, Function, Apple Health, and Android Health Connect; new Agent Skills support FHIR development and prior-authorization review. Life sciences additions connect Claude to Medidata and ClinicalTrials.gov while extending support from preclinical research toward clinical trial operations and regulatory work. The announcement presents Claude Opus 4.5 as a major step in agentic performance on detailed medical and scientific simulations and says its extended-thinking mode improves correctness on honesty evaluations, while emphasizing opt-in permissions, user-controlled access, no training on health data, contextual disclaimers, and referral to healthcare professionals.
Anthropic launched Claude Science, an AI workbench where life sciences researchers run computational workloads from conversation with Claude. The workbench addresses the fragmented toolchain of local machines, HPC clusters, and cloud VMs by centralizing execution in one place. Modal integrates with Claude Science as the compute backend, routing GPU and CPU-heavy workloads to Modal sandboxes automatically and fanning out parallel tasks like virtual screening across hundreds of containers to reduce hours to minutes. Researchers can prompt for tasks such as predicting GFP structure, and Claude writes the folding code, runs it on a Modal GPU, and returns the structure with confidence scores inside the conversation, with Modal handling scheduling, shared storage, and reproducible environments. Modal is committing up to $100,000 in compute for the Claude Science Cohort, with 500– 2,000 allocations per project.
