Data integrity and data quality are critical success factors for artificial intelligence (AI) and machine learning (ML) solutions in life sciences. Simply performing computer system validation or managing computer systems under CGMP conditions is not enough to ensure data integrity and data quality for data sets where AI/ML is intended to be applied.
In this first of what will be a two-part article, USP's Fouad Atouf highlights the challenges presented by the FDA’s newest guidance while remaining optimistic that the large amount of data recommended today will open doors to more efficient development in the (hopefully) near future.
Despite the importance of the process the FDA is outlining in the guidance, I’ve surprisingly heard little chatter — positive or negative — about what the agency is now outlining and what this may mean for biosimilars and the biosimilar regulatory paradigm moving forward. Here are a couple of the biggest takeaways to note.
Though there is a large handful of countries that, to date, don’t have biosimilar pathways established, a few countries have been slowly gearing up to be leaders in paving the way for biologics and biosimilars. In this article, I’ll discuss the potential of these three markets, as well as the business considerations Challand highlighted for companies considering entering the MENA region.
Throughout her presentation, Challand gave us a good look at the current state of the biologics market in MENA and the ongoing educational and collaborative efforts that could help shape the markets in this region. She also shared several important considerations for regulators and biosimilar companies looking to expand their business to MENA.
Though the FDA has taken great efforts in the past year to stand up for biosimilars and establish the BAP, one expert argues the agency can do more to confidently and simply underscore the quality of biosimilar products and to reconsider the need for the additional studies required of biosimilars, especially — but not just limited to — clinical studies.
Data integrity and data quality are critical success factors for artificial intelligence (AI) and machine learning (ML) solutions in life sciences. Simply performing computer system validation or managing computer systems under CGMP conditions is not enough to ensure data integrity and data quality for data sets where AI/ML is intended to be applied.
Measurable benefits of off-site module construction are becoming more evident, and it is emerging as a viable method for delivering a greater degree of predictability. Furthermore, market constraints driven by shortages of craft labor, lagging productivity, project complexity, and competitive forces are contributing to biopharma’s move toward modularization.
How can the industry improve the quality of its products? The first tactic could be to increase the frequency of vendor inspections, using internal quality control programs to inspect suppliers to assure compliance with the necessary supply agreements and adherence to appropriate manufacturing practices, including GMPs.
The number of new chemical entities gaining FDA approval more than doubled from 2017 to 2018. Global R&D spending increased 3.5%. The pipeline is strong, but how many innovations are actually reaching patients?
FDA enforcement for failures in data integrity and data governance began almost 20 years ago, and these areas remain as enforcement initiatives of the FDA and other global health authorities to this day. In 2018, however, we may have turned a corner.
Airflow visualization testing, conducted as part of a routine review program, can help assure that aseptic filling areas remain under a state of proper control.
Having a sound logistics strategy to ensure that a living drug is delivered to the right patient at the right time, location, and temperature is essential to patient safety and product effectiveness.
Over the years, adoption of single-use has emerged as one important strategy for improving downstream and upstream processing while avoiding the downsides of traditional stainless-steel bioreactors.
While QbD evolves from good practice to agency requirement, how can sponsors ensure that rigorous, scientific risk-based approaches are used to bring better and safer therapies to market faster?
As India’s biosimilar market moves toward a promising future, it is important to gain an overview of the current regulatory and clinical expectations in India for biosimilar products.
Scale-up and technology transfer of lyophilization processes remain a challenge, but recent advances in steady-state computer modeling and bench-scale lyophilization practices are driving process optimization with minimal drug substances.
Unexplored and emerging markets are an attractive prospect for biopharma companies looking to expand. But when it comes to ensuring success, what’s the wisest way to invest?
