Friday, May 10, 2019

Post 3 of 6: Central role of mechanistic modeling in Chemical Development

Chemical Development is a complex and challenging undertaking, involving a large effort from multi-disciplinary teams, sometimes battling Mother Nature, with compressed timelines and limited material for experimentation.  There is a broad spectrum of approaches to this challenge, including new lab instruments, use of robotics and automation, outsourcing certain types of development or operations and use of statistical and mechanistic modeling.  Companies also experiment to find the best organization structure for this function and frequently separate departments specialize in Analytical (Chemistry) Development, Chemical (Process) Development, Technology Transfer and preparation of Regulatory filings.  Collaboration among these groups helps achieve development goals.

Figure 1 (click to enlarge): A simplified representation of chemical development today, including the scale and locus of statistical and mechanistic modeling
Figure 1 is a much simplified graphical representation of the activities involved.  There is a large reliance on experiments.  Groups involved in process definition and optimization are currently the main users of both statistical and mechanistic modeling.  Technology transfer increasingly involves working with external partners remotely.  Data search and gather, including data integrity reviews and preparation of regulatory filings, are mostly manual processes.  The disparate nature of activities and the needs for specialization make them somewhat siloed, with risks of duplication and dilution of effort.  For example, an experimental program may be repeated if the first program missed some key information; or repeated by a CRO to answer new questions that have arisen; or repeated by a CMO in order to accomplish successful tech transfer.  None of these data may be harnessed effectively and shared to answer future questions.

Leading companies are changing their approach to chemical development and bringing mechanistic process modeling on stream earlier and more centrally than before.  The idea is not new but advances in a range of technologies (see earlier posts) and the momentum of 'Industry 4.0' are helping to fuel the transformation.  At a task level, using a model to design the right experiments reduces overall effort.  At a project level, the model provides a place to capture the knowledge and reuse it in future.  At an organization level, modeling provides a structured, reusable and digital approach to information sharing and retrieval.  For example, questions can be answered in real time, without experimentation, interactively when they arise, even live in a meeting or webcon, sparing delays, speculation and doubts, allowing faster progress.

Figure 2 (click to enlarge): Future shape of chemical development activities, with mechanistic process models as the focal point for information capture and reuse.
The pieces in Figure 1 are rearranged in a natural way in Figure 2 as a cycle that captures and makes the most of information generated during each chemical development activity, including modeling.  Additional items have been added to reflect technologies that are relatively new to Pharma, including continuous manufacturing and feedback process control; opportunities to apply either or both of these in chemical development or full scale manufacturing can be evaluated using a mechanistic process model.  Therefore the mechanistic model takes up a central position and is the focal point in the new chemical development process.

It will take some time before Figure 2 reaches its full potential.  The throughput of models in chemical development organizations is already increasing as model building tools become easier to use and more prevalent.  We're delighted to be able to lead the way with Scale-up Suite.

Figure 2 also includes some great opportunities to automate workflows.  We'll discuss some of these in a later post.  

Wednesday, May 1, 2019

Post 2 of 6: A brief history

The Wall Street Journal ran an article in September 2003, entitled "New Prescription For Drug Makers: Update the Plants", comparing and contrasting pharma manufacturing techniques with other industries.  The subtitle ran, perhaps unfairly, "After Years of Neglect, Industry Focuses On Manufacturing; FDA Acts as a Catalyst".

Our DynoChem software entered the industry a few years prior, the prototype having been developed as a dynamic simulator within Zeneca, so that users could "create a dynamic model without having to write differential equations".  We first proved that the software could be used to solve process development and manufacturing problems (e.g. with hydrogenations, exothermic additions), then rewrote the source code and began to add features that made modeling by non-specialists an everyday reality.

There have been many pharma industry leaders who have recognized the potential for modeling to help modernize development and manufacturing.  One example is Dr Paul McKenzie and his leadership team at Bristol-Myers Squibb (BMS) at the time, who cited the Wall Street Journal piece in an invited AIChEJ Perspectives article and also in presentations like this one at the Council for Chemical Research (CCR) in December 2005 - you can get the full slide deck here.

Cover slide from presentation by Paul McKenzie of BMS at CCR Workshop on Process Analytical Technology (PAT), December 13, 2005, Rockville, MD
Today, while the landscape for data storage, sharing and visualization has moved ahead significantly, with the emergence of ELN, cloud and mobile, the chemical and engineering fundamentals of defining and executing a good manufacturing process remain the same:

Some capabilities required to develop robust and scalable processes, from the 2005 CCR presentation
Our Scale-up Suite extends these capabilities to more than 100 pharma development and manufacturing organizations worldwide, including 15 of the top 15 pharmaceutical companies.  This broad and growing base of users, armed with clean and modern user interfaces, calculation power and speed in Reaction Lab and Dynochem 5, provides a firm foundation for the next wave of industry transformation.

We're always delighted to hear what users think.  Here are some recent quotes you may not have seen yet:

  • "If you can book a flight on-line, you can use Dynochem utilities" [we like this especially because we hear that using some other tools is like learning to fly a plane]
  • "Our chemists are thoroughly enjoying the capabilities of Reaction Lab software and are quite thrilled with the tool".

In the next post, we will look at the increasingly central role of mechanistic modeling in process development.

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