The chemical and pharmaceutical processes from the Big Data point of view: a truly innovation

Speech in PharmaProcess,  27th -October-2015
Professionals need a forum where disruptive technologies (like big data, IoT or cloud computing) and the impact they will have on current and future manufacturing supply chain strategies will be discussed in order to improve and maximize industry processes.
What are the challenges in adopting new technologies within regulated environments? How they can create real-time models which allow verification of the process before the outputs of the process are obtained? Could be considered as realistic process the Continuous Process Validation? How the batch manufacturing can be considered as a continuous process rather than a discrete process?

You can download the presentation from this link.

Speech at IL3: Continuous verification and protocols for process monitoring

Big data: The end of the utopy of the continuous process validation
Conference in the IL3 (University of Barcelona)
20th - October - 2015

A process is considered adequately known when:

• All critical sources of variability are identified and explained.
• The variability is managed from the process
• The quality of the product and its attributes can be predicted correctly in the design space established by the materials, the environment and other conditions involved in its manufacture.

Focus production in the knowledge of the processes involved reverts to a drastic reduction of the costs and burden of validation systems, since different options are provided to justify and qualify the different production processes.

Big data and regulated industry: the new paradigm

• Cloud environment can not be compared with traditional systems
• Security access is managed in a different way
• The owner of applications become the end user
• Pricing is by use and service, not by licensing
• The validation concept should evolve to the new reality (GAMP X?)
• The science of processes is not based just in pre-defined parameters (CPP & CQA). All inputs and data can participate.

Nowadays, big data is accepted by Pharma R+D when computing power is required.