Enhancing Life Science Laboratories With Development

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Life Science Laboratories

Laboratories are changing the course of drug development by shortening schedules from years to months, cutting costs from billions to millions, and gaining a competitive advantage by bringing pharmaceuticals to market in months rather than decades. Because of this appealing value combination, investments in digital capability and organizational change should be made.

R&D laboratories have the potential to make a 100x or 1000x improvement in their overall efficiency, and there has never been a time in history when it has been more critical to seize opportunities for change than it is right now. The competition for customers is pushing businesses toward greater efficiencies, but access to essential data might hinder the iterative process of scientific research. The performance of the laboratory will only improve if scalable solutions for linking data to analytical systems are found.

Science Laboratories R&D

The observations lead us to believe that the performance of R&D labs is hindered by the traditional scope set for the lab’s evolution. This scope restricts change to limited work groups and keeps new technologies confined to specific scientific fields. In a research and development environment that is optimized for scientific creativity and productivity, the goal is to provide scientists and engineers with the means to acquire and maintain the skills necessary to accelerate their respective fields of study.

One of the best examples of a research and development environment that has been optimized is a laboratory that uses new technologies to connect with data, automate measurements and data ingestion, and applies artificial intelligence and machine learning techniques to run volumes of iterative tests, capturing the results of these tests as data that is ready for analysis. Scientists working in this kind of ideal environment are working to the best of their scientific abilities and improving scientific knowledge to assist the organization in adjusting to new circumstances and realizing its maximum commercial potential.

Based on the studies and experience in the life sciences industry, researchers have found that the most notable successes can be attributed to concerted efforts to transform R&D holistically as new digital technologies are introduced, and scientific personnel acquires the skills to work nimbly and autonomously. With the help of AI, researchers at MIT were able to find a novel chemical that inhibited the growth of E. Coli bacteria, which might be used as an antibiotic. Through streamlining the interactive process, groundbreaking new computing speeds were achieved, resulting in life-saving discoveries.
Optimizing processes at a research and development lab can have a ripple effect throughout a company.

Digital and Analytics in life Sciences

McKinsey provides a high-level organizational approach in their article “Ten battlegrounds for digital and analytics in life sciences,” where they detail ten “battlegrounds” that offer substantial prospects for value creation in the life sciences industry. McKinsey claims that selecting your battles rather than attempting to fix everything at once will help you succeed in the digital world.

The authors state that in each industry, “specific data sets, data and analytics platforms, analytical models, and digital life sciences experiences for customers and end-users are brought to bear upon a cluster of closely connected digital and analytics use cases.”

But which “platform solution” best lays the groundwork for transformation?

But what kind of collaborator best paves the way for long-term shifts? We see three main pillars supporting the structure, and a specific collaborator is required for a fruitful transition. We focus on the following three criteria for making a stronger bond:

• Alliance focused on the process
• Superiority in Technology
• Human-centered design

Taking the long view and having leadership who is committed to providing governance and funding digital innovation efforts are essential for scaling digital life sciences innovation across the firm. According to Chris Llewelln, Senior Partner at McKinsey in London, “without such sponsorship and a narrative that makes evident the necessity of change, most business executives would continue focusing on short-term profit and loss targets, lacking any motivation to do things differently.” These are the little gains made possible by digital technologies that the company is prepared to scale.

A digital strategy’s goals should inspire the R&D life sciences department to explore uncharted territory rather than settle for incremental improvements. It is a fallacy to believe that value will automatically result from spending money on people, data, and technology. At the outset, one should construct a business case and then evaluate it at regular intervals (at least once every three months) to ensure the value proposition still stands. In contrast to incremental improvements, which often offer a line of sight to value in the near-term, say, the next two quarters, making a convincing business case for possibilities through lab R&D is significantly more difficult.

Life Science Laboratories Platform

The optimization of the life sciences laboratory is a forward-thinking, crucial project. Whether it’s the enabling ‘platform’ or the cutting-edge software solutions that will run on it, it’s crucial that Life science-driven businesses take advantage of these developments as they emerge. It’s crucial that projects focusing on digital innovation provide early business value. Without early success, teams and organizations can lose interest, and management may shift focus to more immediately valuable tools, initiatives, and projects.

Unfortunately, the opportunities made possible by modern digital abilities are often overlooked in favor of the incremental advances these projects, tools, and efforts often deliver, which are typically measured weekly. The life sciences industry’s research and development facilities are ready to adapt. All the efforts start in the research and development lab, where we give scientists access to cutting-edge software and methods.