Industry Stories

The Digital Pharma Labs of Tomorrow: A Sample of Things to Come

This blog has been written with inputs from Qais Malik, Technology Architect, IoT

Pharmaceutical laboratories work with data. Lots of data that needs to be stored, analyzed, shared and retrieved. Data that is critical right from serving the needs of the patient to driving outcomes that insurance companies, government and pharmaceutical companies seek. They also deal with a lot of complex laboratory processes that includes working on fragmented data systems, collection and validation of data from diverse sources, and demands from regulatory bodies for high standards of data integrity. These create a perfect opportunity for pharmaceutical laboratories to consider digitizing the entire laboratory workflow in order to streamline processes, control costs and deliver real-time and accurate information.

Digitalized laboratory environments give meaning to data, which enables "digital moments" where decisions are made at the intersection between people, business systems and connected devices. Combined with analytics, the laboratory equipment, consolidated platforms, and consumables, a digital laboratory can sense, communicate, analyze and act on data in an optimal manner.

Key Trends Encouraging the Move to Digital Lab

  • Addition of lab intelligence to existing electronic data with Data Analysis Algorithms
  • Adoption of mobility for quick and easy access to information on the go
  • A single software suite with capabilities of integrated information solutions and unified platform to avoid manual work and redundancy in process flows
  • Simulation and prediction tools to reduce the iterations for new product development and pilot projects
  • Integration of incongruent and multiple systems using a single platform for a single click access to information and workflow to other systems

Electronic Labs of Today Lack Agility and Accuracy

Today, laboratory equipment feed data to systems where analytics filters it for relevancy; however, humans still interpret most of the results. Automation is often built into laboratory informatics, but the systems are not dynamic or flexible.

For example, if the performance of an instrument has been diminishing, the experimental deviations are typically unnoticed until the results go ‘out of trend’. Historical relationship between an operator and a process is difficult to capture. Mistakes, oversights and challenges are routine even in a paperless or electronic environment, despite using laboratory systems with fail-safe capabilities. While these systems are electronic in nature, legacy architecture and infrastructure prohibit them from adopting true digital capabilities.

The Possibilities of a Digital Laboratory

The following questions while sounding aspirational bring forth the value that digital can drive in laboratories:

  • What if the sample could itself “suggest" the method of testing most compatible to itself?
  • What if a system could predict a preventative measure based on historical data?
  • What if a rule based learning engine could suggest improvements based on an instrument’s performance?
  • What if the systems could predict availability of various instruments based on their workflow?

Digital capabilities can create value across the five most common areas where lab metrics are measured.

  • Innovation – Smart informatics systems suggest new findings, highlight hidden data, and expose new insights that were previously impossible or unanticipated.
  • Data Quality – Digital quality assurance/quality control (QA/QC) systems improve our confidence in instrument data, interfaces, calculations and methodologies leading to a reduction in errors, improving product quality, enhancing Electronic Batch Record (EBR) support, and improving compliance and regulatory adherence. Digital systems lead to a reduction in corrective and preventative action (CAPA) activities, fewer warning letters, and less audit fails.
  • Data Security - A lot of valuable research data is either not protected by patent or are held by sub-contractor clinical research organizations. This raises concerns about third-party assurance and security controls on third parties. Digitalizing labs enables labs to prevent, report, manage and respond to data breaches with the right skills, tools, and processes.
  • Operational Efficiency – Digital Laboratory Information Management Systems (LIMS) help accelerate laboratory test milestones. Organizations improve productivity and turnaround time, increasing customer satisfaction.
  • Costs/Profitability – Laboratories 4.0 (modeled after Industry 4.0) efforts lead to more efficient data exchange, use of laboratory resources, reagents, consumables, laboratory supplies and asset utilization.

Last but not the least, the roadmap to a digital laboratory does not end with adopting systems that support self-learning and analytical capabilities, it involves a cultural change in the way the laboratory staff accesses, monitors and manages the samples and results. They need to reskill and learn new ways of gathering, recording, viewing, retrieving, and interpreting data for a true digital success in the lab.