ALFRED AI

ALFRED AI is WhiteLab Genomics' proprietary AI-Led Framework for Rational Exploration in Drug design — a platform that combines advanced algorithms, curated databases, and cutting-edge computational biology to optimize therapeutic candidates for safety and efficacy. Founded in 2019 and backed by Y-Combinator, WhiteLab Genomics operates at the convergence of AI and biology, with a mission to accelerate and de-risk the development of life-saving genomic medicines across diverse modalities including AAV, lentivirus, and nanoparticles.

The platform is designed for biopharmaceutical companies, academic research institutions, and gene therapy developers seeking to leverage biological data-guided rational design and AI to predict the best molecular constructs in genomic medicine. By analyzing complex biological data through advanced computational methods, ALFRED AI empowers collaborators to achieve breakthrough solutions while saving time and resources in early-stage drug R&D.

Core Application Areas

• Gene & RNA-based therapies — Target Receptors Identification & Viral Vector Design: Supports Tech R&D, In Silico Design, and Wet Lab Validation workflows, with applications spanning CNS, Ophthalmology, Rare Disease, and Oncology therapeutic areas.
• Non-Viral Vector Design: Covers Tech R&D, In Silico Design, and Wet Lab Validation, with a focus on Oncology including solid tumors and in vivo CAR-T cell applications.
• Payload Design: Encompasses Tech R&D, In Silico Design, and Wet Lab Validation stages, targeting Neurology, Cardiac, and Pulmonary indications.
• Bioproduction Optimization: Applies the same three-stage workflow to optimize bioproduction processes, with active programs in both AAV and lentiviral vector (LV) manufacturing.
• Cell Therapy Pipeline: Addresses CAR design and vector development through Tech R&D, In Silico Design, and Wet Lab Validation approaches.

Platform Capabilities

• AI-driven rational design to predict optimal molecular constructs across multiple genomic medicine modalities
• Integration of curated biological databases with advanced computational biology methods
• In silico design capabilities enabling rapid review and evaluation of thousands of sequences and novel combinations
• Optimization of delivery vehicles for nucleic acid medicines, including adeno-associated viral (AAV) vectors with novel tropisms
• De-risking of drug assets by predicting and addressing safety concerns such as cytotoxicity early in development
• Acceleration of clinical and regulatory milestone achievement for genomic medicine manufacturers
• Support for indication discovery efforts across a broad range of therapeutic areas

Workflow Approach

1. Tech R&D: Foundational research and technology development to establish the scientific basis for each program.
2. In Silico Design: AI and computational methods are applied to analyze biological data, model molecular constructs, and identify optimized candidates before laboratory work begins.
3. Wet Lab Validation: Computational predictions are validated experimentally, ensuring that in silico findings translate to real-world efficacy and safety outcomes.

Key Partners and Collaborations

• WhiteLab Genomics collaborates with leading pharmaceutical companies including Sanofi, Debiopharm, and Cytiva, as well as biotechnology firms such as Carbon Biosciences and Siren Biotechnology.
• Academic and research institution partners include Institut Imagine, Institut de La Vision, Généthon, INSERM, and UMass Chan Medical School, spanning indications such as podocytopathies, retinal disease, neuromuscular disorders, and mitochondrial diseases.
• Collaborative projects such as WIDGeT and GEAR demonstrate the platform's application to developing novel AAV vectors with improved tropisms and specificity for hard-to-reach cell types.

ALFRED AI supports a fully integrated discovery-to-development pipeline, combining in silico and wet lab capabilities to accelerate genomic medicine programs across viral and non-viral vector modalities, payload engineering, bioproduction, and cell therapy. The platform is positioned for partnerships with both industry and academic collaborators seeking to bring more personalized, safer, and more effective gene and RNA-based therapies to patients.