There are many innovations taking place in drug manufacturing, driven by advances in technology. Drug companies are exploring ways to incorporate AI, big data, and digitization to increase efficiency. Here are some of the trends for 2020.
Also known as precision medicine, personalized medicine involves adapting medication to conform to the needs of a particular patient and how the patient is expected to respond to the treatment.
These types of drugs are already on the market, and their production is expected to increase by one-third in the next five years.
Although these drugs are effective, they present unique challenges for manufacturers. Among these challenges are fitting production schedules to drugs that are made to order, and using smaller manufacturing facilities for small batches, as opposed to larger places for mass production.
Low Volume Production
Manufacturers are moving away from lower cost, higher volume drug production to lower volume, higher-value manufacturing. Drugs produced in low volume generally involve more complex processes and procedures. Also, because the amounts are so small, it can be difficult to gather the data needed to meet government compliance guidelines. All of this requires greater flexibility on the part of manufacturers.
Manufacturers have also been increasing their efficiency by taking all of their paper record-keeping electronic. They are now using electronic logbooks and batch records, as well as digital SOPs. Digitizing processes makes compliance easier, prevents the loss of data, and improves operations.
Using the Cloud
More drug manufacturers are moving to cloud computing because it is becoming less expensive and more secure. Doing this also enables them to ensure the reliability and soundness of their data, as well as making it easier to share data as the product moves through development and testing.
It also enables drug companies to build computer applications while maintaining stringent controls.
Harnessing Big Data
The goal of drug companies is to build so-called smart facilities, where adjustments can be made as the need arises, quickly and smoothly. Moreover, companies are looking to develop predictive capabilities, the ability to foresee problems that may crop up in the future, and take preventive action.
Doing all this, however, requires large amounts of data covering all aspects of production, as well as the use of artificial intelligence. As a result, drug companies are beginning to develop the infrastructure for big data.
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