While there are many important factors for biopharma manufacturers to consider in crafting a data automation solution, three fundamental tenets stand out:

Garbage in, garbage out: without clean, high quality data, any data-driven system is effectively useless. Data automation solutions need to be accurate and comprehensive when ingesting messy, real-life data, whether from programmatic or paper sources. This means being able to read handwriting, ignore ink blots, correctly interpret different date formats, and determine the difference between the letter “O” and the number “0”. It means being robust enough to handle different versions of an API and recognize different versions of the same form automatically. It means dealing with crossed out and corrected paper form entries – as well as corrections to ingested data, in a GMP-compliant way. And it means preserving not just the bits and bytes – but extracting the information and context – from the original source as completely as possible. Finally, it means being able to do all of these things robustly and automatically, across a wide variety of input streams that may evolve over time.

The end goal of data automation is to deliver high quality, data-driven insights that are useful and actionable. One facet of this is timeliness: a GMP-compliant data automation platform can vastly speed up both the digitization and validation of data (through intelligent identification of anomalies and review by exception, for instance). This accelerates access to that data for other teams as well as for regulatory documentation such as batch records, annual product reports, and new drug applications. Another facet of data usefulness is the ability to answer ad-hoc questions (What are the most important factors to maximize cell growth? How much extra capacity do I currently have to produce X? What personnel costs were associated with the production of Y last month?) that allow biologics manufacturers to better understand and optimize their businesses, without requiring a data scientist or programmer. This may involve integrating multiple data sources – for example, being able to combine batch records with data from a supply chain management system to look at the variability of production yield across different suppliers of raw materials. Manufacturers may also want the capability to trigger context-based alerts or programmatically provide third-party analysis software with timely, authoritative, source-linked data, eliminating the need for uncontrolled copying and distribution of data within the organization.

In addition to the above considerations, biologics manufacturers need a data automation solution that protects the company’s intellectual property and bolsters its ability to comply with the complex regulations required by the FDA and other international governing bodies. This means choosing a vendor who works closely with the FDA – one who can offload the manufacturer’s computer systems validation burden while ensuring that regulatory data integrity principles are upheld. Key data integrity capabilities include role-based access control; audit trails and data verification functions; compliant storage and backup across the data lifecycle; and robust physical, operational, and technical security protections.

At Fathom, our solutions are designed specifically for the biologics manufacturing industry, leveraging the latest advances in data automation and artificial intelligence to deliver these core tenets. In doing so, we help our clients unlock the true value of their data – to drive efficiencies, enhance product quality, and boost innovation – in far less time and with far less effort than previously imaginable.