Certified GenAI in Biomedicine & Therapeutics (CGAI-BT) Certification Program by Tonex
Generative AI is reshaping how therapies are discovered, engineered, and delivered. This program equips professionals to apply state-of-the-art GenAI across small molecules, biologics, RNA therapeutics, and advanced cell and gene modalities. You will learn data strategies, model selection, and end-to-end workflows that link design, screening, developability, and manufacturability.
The course emphasizes measurable outcomes: higher hit quality, faster iteration, and informed risk reduction from discovery to CMC. Cybersecurity is treated as a first-class requirement. We address PHI protection, secure model pipelines, dataset provenance, and defenses against data poisoning and prompt injection.
You will map AI evidence to regulatory expectations, create validation plans, and document decisions for audit. By the end, you can translate GenAI capabilities into compliant, secure, and scalable therapeutic programs. The focus is practical, modality-aware, and aligned with industry standards.
Learning Objectives:
- Explain GenAI architectures used in therapeutic design.
- Build datasets and features for chemistry, proteins, and RNA.
- Orchestrate de novo design with multi-objective optimization.
- Evaluate developability, safety, and off-target risks.
- Integrate GenAI into CMC and translational workflows.
- Apply governance, privacy, and cybersecurity controls.
- Prepare regulatory-ready documentation and validation plans.
- Communicate value, risks, and limitations to stakeholders.
Audience:
- Drug discovery and development professionals
- Computational biologists and cheminformaticians
- Data scientists and ML engineers
- Clinical and translational researchers
- Regulatory and quality professionals
- Product and R&D leaders
- Cybersecurity Professionals
Program Modules:
Module 1: Foundations of GenAI for Therapeutics
- Core generative models for bio/chem design
- Molecular, sequence, and structural representations
- Data quality, curation, and governance
- Objective functions and evaluation metrics
- Workflow orchestration across the stack
- Security basics: provenance and access control
Module 2: Small-Molecule Generative Design
- De novo design and library expansion
- Multi-property and ADME/T optimization
- Synthesis-aware generation and retrosynthesis links
- Virtual screening with GenAI-guided priors
- Uncertainty, diversity, and novelty control
- Safety constraints and audit trails
Module 3: Biologics, Vaccines, and Antibodies
- Antigen and epitope design strategies
- Antibody sequence generation and humanization
- Developability and immunogenicity prediction
- Structure-function modeling integration
- Manufacturability and stability assessment
- Documentation for regulated biologic workflows
Module 4: GenAI for mRNA/RNA Therapeutics
- Coding sequence and codon optimization
- UTR and regulatory element design
- RNA structure and stability modeling
- Formulation and delivery considerations
- Off-target and innate immunity risk checks
- IP protection and model artifact signing
Module 5: Cell & Gene Therapy Pipelines
- Guide RNA and donor template optimization
- On/off-target and edit outcome prediction
- Vector selection and payload design
- Cell state modeling and potency metrics
- CMC analytics and release criteria with AI
- Chain-of-custody and traceability controls
Module 6: Governance, Safety, and Compliance
- Model risk management and validation planning
- GxP alignment and change control
- Bias, reproducibility, and explainability
- Privacy, PHI security, and threat modeling
- Regulatory pathways (FDA/EMA) for AI evidence
- Versioning, audits, and documentation practices
Exam Domains:
- Biomedical Data, Representation, and Feature Learning
- Generative Search and Multi-Objective Optimization
- Structure–Sequence–Function Modeling Across Modalities
- CMC, Manufacturability, and Translational Readiness
- Validation, Safety Assessment, and Clinical Evidence
- Governance, Security, and Regulatory Affairs in AI Therapeutics
Course Delivery:
The course is delivered through expert-led lectures, interactive discussions, guided case studies, and curated readings. Participants access online resources, reference templates, and tool walkthroughs to reinforce concepts. Office hours support implementation questions and career-focused guidance.
Assessment and Certification:
Participants are assessed through quizzes, short assignments, and a capstone brief that consolidates methods, risks, and controls. Upon successful completion, participants receive the Certified GenAI in Biomedicine & Therapeutics (CGAI-BT) certificate.
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified GenAI in Biomedicine & Therapeutics (CGAI-BT) Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to accelerate secure, compliant GenAI in therapeutics? Enroll in CGAI-BT today. Build credibility, unlock new modalities, and move safer therapies to patients faster.