Automation & Control / Data Management/Analytics / Contract Manufacturing

Tech transfer: The starting point for full digital transformation

The solution to maximizing speed, accuracy and cost-efficiency is to digitize tech transfer across the entire product lifecycle

By Cathal Strain, President, Neo PLM

In pharma, we tend to discuss technology transfer (or simply “tech transfer”) as a single step in the product lifecycle. The term typically refers to the point when the Process Development group within R&D transfers the process to commercial manufacturing.

However, tech transfer actually occurs multiple times during the product lifecycle — whenever production moves from one location to another, either within the same plant or between sites. Each transfer complicates process knowledge management and the challenge to maintain a “single version of the truth.” Outsourcing production to a contract manufacturer adds further complexity.

The challenge is the same in all cases: ensuring the receiving party understands the process well enough to implement it successfully in production facilities. On paper, this sounds fairly straightforward. In reality, “paper” is precisely the problem, as it remains the predominant medium for executing tech transfers. (That includes electronic documents, or “paper on glass.”)

But if the goal is enabling the rapid uptake of process knowledge, today’s document-based approach to sharing process science and engineering is grossly ineffective. The solution to maximizing speed, accuracy and cost-efficiency is to digitize tech transfer — not only for initial scale-up, but across the entire product lifecycle.

The essential first step in the digital transformation of tech transfer — and, ultimately, all of pharma manufacturing — is to digitize the definition of the product and manufacturing process. To use one of today’s buzzwords, the end-to-end manufacturing process should be defined in a digital model (or design) that effectively serves as a “digital twin.”

That model must be robust, including not only the process science itself (i.e., chemistry or biological transformations) but all information required to support manufacturing operations. For example, the model should define critical process parameters (CPPs) and critical quality attributes (CQAs) to ensure the process remains within acceptable limits. And it must be scalable and flexible to fit various equipment scenarios in different plants.

A digital process design would also provide the framework to seamlessly incorporate contextualized production data into the tech transfer package. Nothing could facilitate the rapid understanding of process knowledge more than seeing how a batch actually ran in the lab or plant originating the tech transfer.

Finally, the digital model would deliver the outputs necessary to drive all manufacturing systems including:

  • Enterprise resource planning (ERP) – with the model providing the bill of materials (BOM)
  • Laboratory information management system (LIMS) – with control points configured from the model
  • Manufacturing execution system (MES) and distributed control system (DCS) – with recipes automatically created and downloaded from the model

This concept is not revolutionary. The discrete manufacturing world has long embraced the idea of structuring all critical business activities around a robust digital definition of the product. It started with computer-aided design (CAD) in the 1980s and extended to computer-aided manufacturing (CAM) and computer-aided engineering (CAE). These technologies now form the core of discrete product lifecycle management (PLM) solutions.

Contrast that digital design-based approach with pharma’s document-centric paradigm. Now imagine tech transfers driven by a comprehensive digital product definition. The receiving party can hit the ground running with a ready-to-use digital model that only needs tweaking to fit into the new manufacturing scenario. This approach offers myriad advantages including:

  • Accelerating time to first manufacturing
  • Enabling “right first time” startups
  • Eliminating error-prone manual processes
  • Reducing costs significantly

Once production begins, the digital process model provides a highly structured framework for collecting and rapidly analyzing batch data. This information can guide not only process improvements, but decisions enterprise-wide as all stakeholders gain access to a single version of the truth. In this way, digitizing tech transfer will lay the foundation for digital transformation across the organization—ultimately revolutionizing all business activities.