This interdisciplinary course explores the frontier of precision oncology, artificial intelligence, and translational entrepreneurship, guiding learners through how scientific discovery becomes clinically meaningful and socially responsible innovation. You examine how molecular profiling, machine learning, immunotherapy, and digital health platforms are reshaping cancer care, from early detection to adaptive trial design, and from underserved populations to scalable solutions.
Beyond technical understanding, the course invites you to think carefully about equity, data justice, and the ethics of innovation. You learn to evaluate evidence, recognise uncertainty, and design strategies that are not only scientifically credible, but aligned with real-world constraints, patient safety, and public trust.
This course provides a research-informed and clinically aligned exploration of personalised oncology, with an innovation lens. Learners explore:
Learners participate in a Cancer Innovation Sprint, working in cross-disciplinary teams to develop:
Teams receive structured feedback from experienced reviewers, which may include clinicians, AI scientists, governance professionals, and venture advisors (either real or simulated, depending on cohort and availability). Where appropriate, learners may have the opportunity to share their work in an internal showcase or leadership-style forum.
By the end of this course, learners will be able to:
At Afer*Nova, each programme is designed to combine academic depth with real-world relevance, supporting learners to connect scientific understanding with applied decision-making. The curriculum is refreshed regularly in response to developments in biomedical science, innovation ecosystems, and public governance debates.
Programmes are intentionally cross-disciplinary, supporting learners across health sciences, engineering, policy, and entrepreneurship.
Learners begin with flexible learning modules that build a strong knowledge base through:
This phase supports independent learning while building confidence in core concepts.
Learners participate in mentor-guided workshops focused on applied learning, featuring:
These sessions support critical thinking, collaboration, and strategic communication.
Programmes are periodically refreshed to reflect:
This helps ensure learning remains current, adaptable, and aligned with evolving needs.
At Afer*Nova, teaching is designed to help you think like a translational scientist and innovator. You are guided to connect molecular evidence to clinical reality, and to reflect on the ethical and societal consequences of building new technologies in healthcare.
Learning includes case-led masterclasses, interactive labs, ethical simulations, leadership challenges, and structured mentoring. Assessment supports both understanding and applied judgement and may include critical reflections, research reviews, prototype or concept briefs, impact reports, peer feedback, oral presentations, and innovation sprint outputs. Final submissions often take the form of a portfolio, project report, or policy brief, supported by structured feedback.
This programme is positioned at the frontier of modern oncology, where molecular medicine meets computational science, and where translational ideas must become scalable, ethically grounded solutions. You learn how to move between domains: from biological mechanism to data interpretation, from clinical constraints to governance realities, and from scientific promise to real-world implementation.
Rather than treating cancer biology, AI, and entrepreneurship as separate tracks, the course integrates them, so you learn how complex systems actually function in practice, and why judgement matters as much as technical skill.
Learners are supported through structured mentoring and detailed feedback from experienced educators and professionals across oncology, AI, governance, and venture design. Mentoring is delivered through supervised teaching and small-group learning, with individual feedback where appropriate. The aim is to help you develop scientific reasoning, systems-level thinking, and narrative clarity, so you can communicate complex ideas to diverse audiences and make evidence-led decisions under uncertainty.
The programme centres on active engagement with real challenges in cancer science and innovation. Through the Innovation Sprint, teams conceptualise and present translational solutions, which may include diagnostics for underserved settings, ethically governed AI screening systems, adaptive trial designs, or equitable market strategies. Projects are evaluated through structured feedback designed to strengthen reasoning, feasibility, and responsibility, reflecting the kinds of decisions made in real translational environments.
Learners may have the opportunity to develop dissemination-ready outputs that contribute to broader scientific and public conversations. Subject to academic quality standards and supervisory or editorial review, selected outputs may include:
Learners who successfully complete programme requirements receive a formal certificate of completion. Where appropriate, and subject to meeting defined performance and professional standards, students may be eligible to request a personalised academic reference letter at the discretion of the supervising faculty member.
Subject to performance, quality review, and supervision, learners may have the opportunity to:
If you wish to enroll in the course, please click the ‘Register Now’ button. Our team will reach out to you after reviewing your academic qualifications.