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In recent years, problems with data integrity have become a key concern for global regulatory agencies. In 2015, the UK Medicines and Healthcare products Regulatory Agency (MHRA) issued a Guidance for Industry on Data Integrity . In 2016, FDA issued a Data Integrity and Compliance With Drug CGMP Questions and Answers Guidance for Industry . The FDA wrote, “The guidance has been developed in response to an increase in findings of data integrity lapses in recent inspections. FDA expects that all data be reliable and accurate. CGMP regulations and guidance allow for flexible and risk-based strategies to prevent and detect data integrity issues.” With this problem area identified and an area of focus for regulatory agencies, it is wise for firms to ensure CGMP compliance in this critical area.
The complexity of molecular entities in clinical development has increased in recent years. We’ve been fortunate to be involved in the CMC development of some drug candidates that posed some interesting challenges, such as complexity of structure, number of asymmetric centers, length of synthesis, lack of UV chromophore, amphiphilic nature, and so on. One interesting analyte posed a unique challenge. A large broad unknown HPLC peak appeared chromatograms during its analysis. Since this was an API in development, it was imperative to solve this problem. By considering the analyte’s chemical structure and how it might interact with a sub-ppm impurity in the mobile phase modifier led us to the answer .
An error was made in the structural analysis of an anticancer drug candidate, ONC201. The incorrect structure (b, above) was included in the sponsor’s (Oncoceutics’s) patent in 2014. Researchers at The Scripps Research Institute found the correct structure (a, above) and patented it. A years-long legal dispute ensued . Ultimately, Oncoceutics licensed the patent from Scripps in 2019, and Chimerix acquired Oncoceutics in 2021 . This error in structure analysis was costly and underscores the importance of thorough structure analysis. Obtaining 2D NMR data (e.g., NOESY and HMBC) on ONC201 and conducting careful data interpretation would have likely shown the depicted correlations, enabling the correct assignment and circumventing the very costly consequences.
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