How can artificial intelligence help pharmaceutical sponsors identify potential shortages of comparator drugs?

Comparator drug sourcing involves securing specific pharmaceutical products across different markets while managing batch requirements, documentation, and study timelines. A product available today may become difficult to obtain months later, particularly when enrolment increases or market availability changes.

However, whilst AI can help to identify risks early, there will need to be different capabilities to identify potential shortages and secure the right alternative.

Where can you implement technology to make informed sourcing decisions? Where is expertise needed?

Why Comparator Drug Sourcing Is Difficult to Predict

Clinical trials are not always predictable.

At one study site, patients might be recruited more quickly than expected, which will require more of the product. At another site, patient recruitment might be slower than expected, leading to excess stock nearing its expiry date.

External factors also have an impact. Quotas, limited distribution and import requirements could mean there is less comparator available in certain countries.

For example, if a multinational study requires a particular comparator formulation, whilst increasing patient recruitment, there might be less comparator available in the preferred country.

This can be difficult to identify with information being held by multiple different sources. Using AI to analyse can help identify these signals.

How AI Could Improve Comparator Drug Sourcing

AI-based tools can analyse historical data alongside current operational information to identify patterns that conventional forecasting may overlook.

A May 2026 EY analysis of AI-enabled clinical trial supply chains highlights opportunities for technology-supported decision-making in predictive demand planning, supplier risk assessment, inventory management, and distribution.

Four applications are particularly relevant to comparator sourcing.

1. Predicting Comparator Supply Shortages

A shortage rarely becomes visible only when inventory reaches zero.

Changes in enrolment, consumption rates, and procurement lead times may indicate potential supply pressure earlier.

AI-supported systems could analyse these variables and flag situations where projected demand exceeds available stock.

Procurement teams could then review quantities, contact suppliers, or investigate alternative markets before the shortage affects study operations.

2. Improving Procurement Forecasts

How much comparator should we order?

Ordering too little could lead to urgent ordering and ordering too much may result in expiry of unused product.

Using predictive forecasting can enable sponsors to explore various scenarios for patient recruitment and update their ordering strategies.

This can be based on updated data instead of original estimations.

This ensures there is enough comparator drug available while limiting unnecessary over-ordering.

3. Identifying Sourcing Market Risks

Comparator availability varies across countries. Some markets have limited quantities, while others involve distribution restrictions or longer procurement lead times.

Given reliable supplier and market data, AI tools could identify patterns indicating where sourcing constraints may emerge.

Such information could help teams prioritise market assessments.

However, actual availability, batch specifications, and remaining shelf life must still be confirmed with qualified suppliers.

4. Supporting Distribution Planning

Procurement is only one part of comparator supply.

Products must also reach study sites under suitable storage and transportation conditions. Customs procedures, temperature requirements, and delivery schedules introduce further complexity.

Predictive logistics analysis could identify routes associated with delays, allowing teams to consider contingency arrangements earlier.

Why Human Expertise Still Matters

It can speed up the analysis process.

However, sourcing pharmaceuticals will require proper validation of supplier qualifications, product authenticity, track & trace, and regulatory documentation. Even if an alternative market/batch is found using a predictive system, it must still be suitable for the study.

Data accuracy is also key. If you have incomplete stock data or out-of-date supplier information, it can mean that your predictions are incorrect.

The real opportunity for sponsors lies in using your technology insights in combination with your procurement knowledge.

AI might find an issue, but you will need qualified sourcing staff to look at your options.

Planning Comparator Supply for Your Next Clinical Trial?

Country-specific sourcing requirements, batch availability, and procurement timelines can influence study planning.

Neunco supports sponsors and CROs in evaluating comparator sourcing options across international markets.

Discuss Your Comparator Sourcing Requirements

How Neunco Supports Comparator Drug Sourcing

As clinical trial supply planning becomes more data-driven, reliable pharmaceutical sourcing capabilities remain essential.

Neunco provides Comparator and Reference Listed Drug (RLD) Sourcing services for sponsors and CROs managing international procurement requirements.

Its services accommodate country-specific sourcing, single- and multiple-batch orders, particular batch numbers, varying pack quantities, and longer remaining shelf-life requirements.

Neunco’s infrastructure includes an EU GDP-certified warehouse in the Netherlands and a licensed distribution centre in New Jersey, USA. Its verified storage network offers more than 20,000 pallet positions across ambient, refrigerated, and frozen conditions.

Qualified logistics partners support international temperature-controlled shipments.

Neunco also provides order-status tracking, enabling clients to monitor procurement progress throughout the sourcing process.

While emerging technologies may improve supply forecasting, Neunco’s established capabilities centre on sourcing expertise, procurement coordination, storage, and global distribution.

The Future of Comparator Sourcing: Prediction Meets Procurement

AI could change how pharmaceutical sponsors anticipate shortages, evaluate demand, and manage comparator inventory.

Yet predicting a supply risk is only the beginning. Turning that information into an effective procurement decision requires verified product availability, qualified suppliers, and coordinated distribution.

For comparator sourcing for clinical trials, the strongest approach combines early visibility with practical sourcing expertise.

Technology can help identify emerging challenges. Experienced teams determine how best to respond.

For related insights, read Neunco’s article on common clinical trial supply delays and how to address them.