We summarise a recent article, published in Drug Discovery Today, that summarised how the increasing volume and availability of data throughout the drug pipeline can provide insights into medicine acceptability and aid informed drug product design of future, acceptable medicinal products.
Big data in drug development
Data helps inform the four stages of pharmaceutical product development. This is being increasingly driven by ‘big data’ – extremely large datasets that can be computationally analysed to reveal patterns, trends and associations. Various platforms and technologies are already being harnessed within pharma to collect and analyse big data, particularly artificial intelligence.
A successfully developed drug delivery system has several key considerations: acceptability, efficacy, manufacturability, and safety. In recent years, acceptability has gained substantial focus from pharma and regulatory bodies. Acceptability requires recognising and considering characteristics of both the end-user and the medical product.
In particular, experts can harness digital technologies to collect medicine-acceptability big data. This will support real-time, informed drug product development while minimising issues of medication rejection.
Medicine acceptability
Big data-informed drug development with digital technologies has the potential to reduce time and costs. Below are the individual phases of drug development where big data for medicine acceptability exists.
- Preclinical trials – Sensory analysis studies can help assess the acceptability of designed formulations. In addition, researchers can use large datasets to create predictive models capable of selecting the most acceptable formulation.
- Clinical trials – Phase I – Data can enhance predictions of the overall acceptability and tolerability of a drug product in healthy participants.
- Clinical trials – Phase II and III – These phases are likely to generate the greatest volume of medicine-acceptability data. This is because of the recruitment numbers and the possibility that the disease state may alter characteristics important in the acceptability profile.
- Marketing authorisation application and approval – Digital technologies can accelerate the filing of new applications.
- Post market surveillance – This phase allows for extensive data collection because of the further population size and diversity as well as the increased time for data collection. The two main forms are monitoring of adverse drug reactions and detection of falsified medicinal products.
Conclusion
As regulatory bodies increasingly recognise the importance of medicine-acceptability data for drug development, pharma must continue to shift away from traditional practices to electronic technologies. The collection of real-world, real-time, clinically relevant data will help inform drug development and reduce medication rejection.
Image credit: Image by Arek Socha from Pixabay
