Communicate the purpose of AI in drug discovery to those who have to comply with it.
Artificial Intelligence Applications in Drug Discovery and Trial Acceleration
A structured, applied course in AI in drug discovery — designed to be used the week you return.
📍 Abu Dhabi🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
The constraint on AI in drug discovery is rarely the model or the platform — it is the data and the operating discipline behind it. The distance between a working prototype of drug discovery and a system the business can depend on is where most budgets disappear. This programme builds this strand of digital and data-driven work from first principles, without padding and without omitting what matters. It is designed for mixed groups, so that AI in drug discovery is examined from more than one functional angle. Most organisations already have a policy on the practice within digital and data-driven work; far fewer can show it working. Participants test their assumptions about drug discovery against scenarios designed to break weak ones. Across sectors, teams that rehearse AI in drug discovery outperform teams that only plan it. Participants gain a clear basis for measuring what drug discovery has actually achieved. The course ends by identifying what the participant will stop doing to make the digital and data-driven work discipline sustainable.
Expected Learning Outcomes
Establish monitoring that detects model or service degradation in drug discovery before users report it.
Build the internal capability for AI in drug discovery rather than depending on external support indefinitely.
Build a concise delivery roadmap for drug discovery that colleagues can follow without further explanation.
Agree the retirement plan for the legacy process AI in drug discovery replaces.
Establish version control and rollback for every component of drug discovery that reaches production.
Set retention, lineage and deletion rules for the data flowing through AI in drug discovery.
Who Should Attend
Data and analytics leads responsible for the pipelines behind AI in drug discovery.
Solution architects designing how drug discovery fits the existing estate.
Quality staff verifying that AI in drug discovery performs as designed.
Public sector digital leads applying drug discovery under procurement and privacy rules.
Risk and compliance staff assessing the controls around AI in drug discovery.
Experienced practitioners formalising an approach to drug discovery that has grown up informally.
Course Modules
AI in drug discovery: vendor selection and avoiding lock-in
2 sessions · 8 pointsSession 1The data question everyone skips at the start of AI in drug discovery
- Verify six months later that changes to AI in drug discovery have held.
- Confirm the retention and deletion rules applied to data inside drug discovery.
- List the data sources AI in drug discovery consumes and confirm each has a named owner.
- Set the metrics that will show whether drug discovery is drifting from its intended behaviour.
Session 2Building lasting competence in drug discovery
- Plan the sequence in which improvements to AI in drug discovery will be introduced.
- Decide which legacy process drug discovery retires, and set the date.
- Arrange the handover of AI in drug discovery so capability survives staff changes.
- Define the exit route from the supplier supporting drug discovery.
Drug discovery: cost, licensing and total running expense
2 sessions · 8 pointsSession 1The pilot that actually settles the argument about drug discovery
- Identify the skills the team lacks to operate AI in drug discovery independently.
- Plan how drug discovery is versioned and how a bad release is rolled back.
- Agree who is on call for AI in drug discovery outside working hours.
- Record the reasoning behind each architectural choice in drug discovery.
Session 2Choosing a supplier for drug discovery without being captured
- Name a single owner for each element of AI in drug discovery.
- Assign responsibility for keeping documentation of drug discovery current.
- Build the user briefing that explains what AI in drug discovery does and does not decide.
- Estimate compute and licensing cost for drug discovery at expected and at peak load.
Drug discovery: security, privacy and regulatory obligation
2 sessions · 8 pointsSession 1The governance drug discovery needs and the governance it does not
- Rank the weaknesses in AI in drug discovery by consequence rather than by ease of fixing.
- Distinguish symptoms from causes when drug discovery underperforms.
- Set out how exceptions to AI in drug discovery are requested and approved.
- Record what was learned when drug discovery did not go as planned.
Session 2Reading the current state of AI in drug discovery honestly
- Measure the current quality of the data feeding AI in drug discovery before assuming it is usable.
- Identify every system drug discovery must read from or write to.
- Prepare the response for the most likely failure in AI in drug discovery.
- Specify the fallback path when drug discovery is unavailable.
Drug discovery: from pilot to production
2 sessions · 8 pointsSession 1Keeping drug discovery alive after the initial push
- Map the handovers in AI in drug discovery between functions and secure them.
- Identify the data already collected that bears on drug discovery.
- Establish who is informed, consulted and accountable in AI in drug discovery.
- Build the competence framework that supports drug discovery.
Session 2Proving drug discovery paid for itself
- Test AI in drug discovery against edge cases drawn from real historical records.
- Agree the indicators that will show whether drug discovery is improving.
- Establish the boundary of AI in drug discovery and record what sits outside it.
- Assess the regulatory obligations drug discovery triggers in each jurisdiction.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
We will contact you within one business day to confirm.