Considering how much in flux the pharmaceutical industry is at the moment, predicting the future can be tricky. Some trends seem more obvious than others; streamlined production seemed like the obvious trend before multi-nationals discovered India and China (albeit a few centuries after Marco Polo). Application of new process analytical technology (PAT) programs slowed down when it was seen that the traditional approaches could be cloned in China, using lower-paid workers.
Nonetheless, the realities of supply-chain integrity and a rising standard of living in these developing countries will once again pressure pharma and biopharma companies to adopt modern PAT controls of their production lines. When the cost of production in, for instance, China comes within a certain percentage of the cost of production in the US, the added burdens of shipping and testing imported drug products will obviate the savings. There will be far greater savings associated with streamlining production at home than by outsourcing.
Prediction #1: PAT will become ubiquitous and, eventually, the law.
Raw materials used in pharmaceutical production will not be modified to suit the production of drug products, simply because the Pharma industry is not the largest customer for most materials (aside from API, of course). As a consequence, when Pharma is using PAT, the knowledge needed to control the processes will force the companies to do more and more characterization of non-API raw materials. This will include things common to API, such as polymorphic form, crystallinity, flowability, crushability, porosity, surface area, and similar physical parameters. This will lead to a better understanding of how solid dosage forms are made.
Prediction #2: QbD will become a necessity to remain competitive, not merely “a nice idea, if you have time.”
And, as I am seeing here at EAS, there is a trend of partnering of smaller instrument and software companies. [For reference, all the instrument companies in the world have a smaller gross income than is brought in by Lipitor.] The software involved for PAT needs to complex, combining various signals such as pH, temperature, power consumption, various spectra, to name some inputs. Since most instrument companies are relatively small, the burden of writing necessary software is a financial strain. Thus, companies specializing in software (statistical and Chemometric) will join forces with hardware and engineering firms to offer “solutions” instead of just pieces of the puzzle.
Prediction #3: the classic paradigm of analysts buying equipment and software and having in-house personnel install them will morph to “full-service” companies installing, calibrating, and maintaining the process monitors for PAT.
Last but not least is a guesstimate of the number of companies who will exist. The steady march of mergers and takeovers among the giants is obvious and needs no commentary from me. The number of generics is what I will comment upon. With the large number of blockbuster drugs coming off patent and the growth of HMOs and states demanding generic substitution, generic companies have grown almost exponentially.
However, with the advent of PAT and, eventually, real time release testing (RT2), things may well change to a different trend. At the moment, all a generic company need do is prepare a single lot of their version of a brand-named product, show that it meets release specs and it is approved for sale. With RT2 there will be no “release specs” per se; the products will be released on compliance with design space measurements. Unless the laws regarding this process are changed, companies are not required to tell generics how they produce their products, merely disclose the active and release specs. With no release specs, the generic houses will be required to perform in vivo/in vitro correlations. These clinical tests will be time consuming and expensive.
Prediction #4: The absolute number of generic companies will shrink drastically; they will either merge to form bigger generics (able to afford iv/ivc testing) or simply fade away.
Whichever prediction may or may not come true, the pharma industry of tomorrow will not look like the industry of today.
