Novel strategy to improve quality checking of generic drugs

New Delhi: Generic drugs are cheap and effective alternatives of branded drugs but require strict quality and risk assessment. Based on the lately endorsed “quality by design” (QbD) concept, researchers from China have developed a new assessment strategy that can be used to check quality of generic drugs developed by varying processes. The strategy is likely to improve the regulatory and decision-making aspects related to pharmaceutical products.

As the cost of branded drugs is increasing faster than ever, challenging the purchasing power of patients, the demand for generic medicines is on the rise. Generic medicines, the patent-expired versions of the branded drugs, contain the same active ingredients and intended use as the branded ones but are much cheaper than the latter as the manufacturers do not need to develop or market them as new drugs. Nevertheless, before being available in the market, generic drugs require to pass the same quality standards as branded ones.

In China, the landscape of the pharmaceutical industry is undergoing rapid evolution. Riding on the power of its domestic generic pharmaceutical products, the country has emerged as one of the largest generic drug markets in the world. This warrants new regulations to evaluate generic drug consistency and to enhance the international competitiveness of the country’s domestic pharmaceutical industry. However, National Evaluation Sampling and Test Project (NESTP), China’s existing domestic generic drug evaluation information source, fell short of meeting the fast-changing drug market requirement. To put it simply, drugs imported from the EU and the USA are typically manufactured through production processes and process controls different from the domestic drugs and hence were not suitable to be evaluated by NESTP.

To bridge this gap, a group of researchers from China now has come up with an innovative strategy that would enable the quality evaluation of generic drugs developed by different processes. The study, led by Professor Changqin Hu of the National Institute for Food and Drug Control and Professor Xiaomei Ling of Peking University, was published in Journal of Pharmaceutical Analysis. This paper was made available online on 4th November, 2020 and was published in Volume 11 Issue 5 of the journal on 31st October 2021.

The researchers designed their study aligning with quality standards of current Good Manufacturing Practice that stressed the “QbD” concept instead of the traditional “quality by test” approach. Prof. Hu explains, “According to QbD concept, quality of drugs can be maintained by ensuring the quality during each step of the design, development and manufacturing process. To develop an evaluation strategy that would assess the commonalities among different processes of generic drug development, we aimed to define universal indicators and methods to characterize different processes used for the same pharmaceutical product.”

Fortunately, a whole gamut of information related to the drug development processes was documented and available in NESTP and other literature, serving as the resource for designing the desired computational model for quality assessment. Based on this information the researchers developed an evaluation process called “population pharmaceutical quality assessment” for mining the process information related to sample-population quality and investigating intrinsic links between QbD elements. The strategy formulated in this way was found to be adept in the quality and risk assessment of the pharmaceutical process. Prof. Ling elaborates, “Our method provided a scientific tool for objectively and comprehensively evaluating quality consistency and promoting the regulation status of domestic generic drugs.”

To demonstrate the applicability of the new strategy, the researchers performed quality consistency assessment of generic ceftriaxone sodium injections and process risk assessment and population quality trend tracking of generic aztreonam injections. Both assessments offered satisfactory results. “The newly developed method emerged as an effective and economical means to improve product quality by discovering key issues in drug quality evaluation through data mining. Moreover, the method would likely facilitate timely prediction of various hidden but avoidable quality hazards, serving the regulatory perspective,” Dr. Zhao surmises.

The researchers are hopeful that by leveraging the continuous addition of data in the knowledge base, they can improve their strategy further for superior decision-making regarding drug regulation.