A couple of years ago, I published a post on 5 API Regulatory Challenges to Avoid, and it was interesting to look over the list and contemplate what updates I’d suggest.
While all of the original points remain challenges during API drug development, an updated list in 2016 would include the rise of data analytics and the adoption of Quality by Design (QbD). Others, such as weak impurity profiles, proper route selection and weak impurity characterization remain front-and-center challenges for many pharma companies today.
- QbD: All Aboard.
QbD isn’t going away – quite the contrary, it’s just starting to make its presence felt. Since Merck’sJanuvia became the first product approved based on a QbD application in 2006, Quality by Design (QbD) has been setting itself deep into the pharma development and manufacturing industry – and to largely positive effect. (Our experience at Neuland with QbD has been positive, as well).At its core, QbD aims to maximize product safety & efficacy while improving the underlying manufacturing process. Quality by Design is proving itself to be an effective framework, and pharma sponsors are increasingly looking for contract research & manufacturing firms who are QbD-capable. - Data – it ALL Matters.
We are deep into the era of Big Data analytics. The amount of data we have available to us is enormous, and growing – sometimes uncontrollably.But data is your friend, and it holds the answers to critical regulatory decisions that companies face. Data analytics can help deliver accurate, rapid decisions during discovery, development, manufacturing, clinical stages and ultimately commercial post-market.Given that data management & analytics are increasingly essential to the pharma industry, they must be given strong consideration across the entire spectrum of the drug lifecycle.
These last four challenges from my previous list still apply:
- Route Selection
Choosing the right synthesis route still remains a top priority, given the cost of “getting it wrong” (or – and perhaps more likely – developing a longer, less cost-effective route with potential challenges).Chemical synthesis route scouting is intended to stave off production problems – genotoxic or other impurities, overuse of chemicals and reagents (and the accompanying EHS issues that may arise), manufacturing times & capacities…route scouting impacts a number of critical points in the manufacturing chain, and can have an outsized impact on them.Read more about Route Selection in: The Benefits of Synthesis Scouting. - Incomplete Stability Data
New APIs mean a lack of stability data, and that doesn’t bode well for regulatory success…or established expiration dates. Make sure you’ve considered this, and your supplier/partner can handle any studies that need to occur.If outsourcing stability testing to a third party, it’s important to ensure the smooth transfer of data and knowledge from your supplier to the testing provider. Make sure stability studies are performed in accordance with ICH guidelines and other protocols. - Weak Impurity Characterization
Analytical and other testing methods must be fully developed and validated. Remember: identifying, characterizing and synthesizing your API is crucial…but so is identifying, characterizing and synthesizing the impurities that typically surround it. Bottom line: the impurity profile matters to your API’s regulatory success. - Problems with Genotoxic Impurities
Genotoxic impurities continue to be a major source of regulatory headaches. They are often cited as one of the reasons clients approach Neuland for alternate route scouting & selection services. But GIs are more than just a manufacturing challenge: analytical methods need to be highly-sensitive to detect them. And while many genotoxic impurities can be avoided, often your manufacturing partner will need to focus on controlling them – whether by adjusting environmental controls, altering purge strategies, using preservatives or another means.
These are some of the top API regulatory challenges we see in the industry today – from the rise of QbD & data analytics to continued challenges characterizing the stability & impurities of new chemical entities.
What would you add to this list?
