Lab of the Future is now

Team Talk

Current Business Goals For Digital Transformation In R&D

Célia Gasselin
Célia Gasselin September 10, 2021

The pharmaceutical industry is undergoing a digital revolution to improve its R&D efficiency and leverage the power of big data to accelerate the time-to-market.

Implementing new, sometimes disruptive, technologies in the lab can give a clear competitive advantage. Several strategies, such as digital lab groups or accelerator programs, have been created to scout for innovative solutions and estimate their potential if scaled up to the entire company. Ultimately, the decision to implement a new technology relies on the alignment between the scientists’ needs and the company’s business goals.

We invited Business and R&D IT experts from BMS, Regeneron, GSK, and Dow to discuss their strategies to ensure alignment between business and lab needs and explain how they evaluate ROI to build a successful business case.


Current Business Goals For Digital Transformation In R&D

Digital transformation is a means to an end, not a goal in itself. However, to achieve many of their business goals, pharmaceutical and chemical companies must implement a full digital transformation.


The principal goal of most companies is to increase R&D efficiency and get new products to market in less time. Through automation and standardization of processes, scientists can start new projects earlier and spend less time curating data or handling mundane tasks, thus speeding up the innovation rate of the company.

Data-driven decisions

A second common goal is to enable data-driven decisions by using historical data to predict future experiments. Gleaning insights from disparate data sets requires building AI/ML models and aggregating the data into queryable platforms.

Data transfer

As data becomes more and more digitalized within each lab, translating the information between the preclinical and clinical domains remains a big challenge.


“All the digital transformations that we do are focused on trying to get insights from our data to make our decisions better, to make our medicines better, to make sure that we’re identifying the right patients who can actually benefit from the medicines. And bridging the gap between what we’ve discovered in the lab and how we translate those discoveries into the clinic.”

Viral Vyas, Lead IT Business Partner at BMS


From Business Goals to Lab Reality: a Top-down or Bottom-up Strategy?

Solutions to achieve those business goals can come from a large-scale analysis performed by the executive team or by asking scientists for their input on problems and potential solutions.

Top-down alignment on objectives

With a top-down approach, once business goals are locked into the roadmap, executives start by identifying potential roadblocks. Then, they list technology solutions that could help to overcome challenges and achieve their business goals. This strategy creates buy-in from the top from the very beginning of the project.


“If it's seen as an IT project instead of a business project, it's probably going to be doomed. “

Terryl Kibodeaux, Director R&D Business Relationship Management at Regeneron Pharmaceuticals


While advocating for a top-down approach, some business partners also strive to be very transparent with scientists and partners in terms of what they are trying to accomplish and how that aligns with the company's business objectives. Moreover, discussions with scientists can help business partners prioritize and allocate resources between different projects.

Bottom-up problem detection

A different strategy consists of exploring small-scale solutions used by scientists to overcome challenges and use that information to identify gaps in the current systems. However, the trap to avoid here is delivering a point solution that is not scalable. Some organizations are entangled with a myriad of legacy systems which are hard to support in the long term. A better approach is to find common solutions or common problems identified by multiple scientists.

“Our job is to find a trend in the gaps and figure out how we solve that trend without getting caught up in the technical debt of managing hundreds of point solutions. “

Simon Cook, Research Scientist and Solution Manager at Dow Chemical


Scouting for Solutions

Reusing technologies

Bringing a new solution to the lab requires not only a plan for implementation but also a plan for long-term support. It makes sense for most organizations to start by looking at how they might reuse existing systems adapted to a different workflow.


“One of the first things we do is try to figure out whether we have something else we can borrow, a system we can import from manufacturing to pre-clinical labs for example.”

Julia Pence, R&D Digital Transformation Portfolio Manager at GSK Vaccines


Change management can help new users to figure out how they can benefit from interdepartmental technology transfers.

By understanding the higher level of each process in terms of data processing, companies can reuse a similar data architecture across departments, favoring data standardization.


“At Regeneron, we have a project which is a data catalog, where we list up for each system all the types of data it collects so that any common data structure between new projects and existing ones can be matched. We use that as a starting point to develop new systems.”

Terryl Kibodeaux, Director R&D Business Relationship Management at Regeneron Pharmaceuticals


Ensuring the best fit

If no pre-existing system can be leveraged, new technologies must be identified to fix the problem. However, it is very important to assess whether a potential technology is the right fit for the enterprise platforms if it can integrate into the global architecture and how it relates to the overall strategy. Scalability of the technology is just as important; the team must establish if any new technology will be able to support multiple processes across the organization to reduce the total number of technologies to be integrated.


“You will try to find the best fit for the organization, which isn't always necessarily the best technology.”

Simon Cook, Research Scientist and Solution Manager at Dow Chemical



Multiple strategies co-exist in terms of testing new technologies. Incubators can be a good source for new innovative technologies. Some companies set up an internal innovation lab with a dedicated team to test new technologies. However, the most classic approach is to run one or more Proof of Concept (PoC) studies with short-selected technologies to evaluate their potential.


“We have a Plan-Build-Run Agile process: we try to identify a Minimum Viable Product that we can gain value out quickly (that’s the build), then we continue to iterate on it (that’s the run).”

Terryl Kibodeaux, Director R&D Business Relationship Management at Regeneron Pharmaceuticals

Enrolling tech champions

A key part of a successful testing process is to identify a team of enthusiastic individuals who are willing to work on the project. Transparent communication with these tech champions about the related business goal is essential to ensure motivation and alignment.


“It is always about the why. Why are we doing this? Why is this technology important to us? And if we are able to articulate and describe it in a way that is receptive, then it makes the whole testing process a lot easier.”

Viral Vyas, Lead IT Business Partner at BMS


Moreover, keeping the executive team updated on the ongoing project will facilitate future conversations about next steps.


Measuring Success

When testing new technology, the team must evaluate its impact on business goals before deciding whether to implement it in the organization.

Value statements

Which measurements will indicate success? What improvements are we looking for? These questions should be answered at the beginning of the testing project and will constitute the core of each business case. The team must work together to identify key performance indicators (KPIs) and milestones that will indicate whether a technology is worth further investigation.

Some organizations choose to avoid measurements such as time savings as it can results in staff reductions. Therefore, it is imperative that all business stakeholders agree on the selected KPIs before trialing any technologies.

Measuring the KPIs

Once the KPIs have been identified, the next step is to establish a strategy to measure them. This can be done in multiple ways: via the technology itself, by staff surveys or on a longer timescale by assessing budget reduction or changes in time-to-market. If the measurements can be extracted from the technology itself (such as the number of requests in a LIMS for example), sharing this success criteria before implementing the technology can make it easier to incorporate an easy readout.

It is important to measure a baseline before the technology is implemented and compare this to the same parameters 3 to 6 months later. This can provide clear information on how the technology has impacted the business goal.

In some circumstances, it might be worthwhile to consider the technology’s impact on subsequent stages of a process. For example, getting feedback from data scientists is very valuable when attempting to measure a technology’s impact on data quality.

“It is part of the Agile process to work hand-in-hand with our modelers and run quick tests to validate our new data systems.”

Simon Cook, Research Scientist and Solution Manager at Dow Chemical



Ultimately, success is measured in term of profits made compared to the costs of development. However, this is not always possible for preclinical research as many products fail before reaching the market.

“The real value of some projects shows up when the vaccine gets to manufacturing, and sometimes, the project doesn’t get through clinical trials. How do you then account for the carbon savings that you found for the vaccine that never went all the way to manufacturing?”

Julia Pence, R&D Digital Transformation Portfolio Manager at GSK Vaccines


In R&D, the common motto is “If we fail, let’s fail fast”. So, another measure of success could be how fast you get to clinical trials and how many attempts you can make in parallel.


Building a Successful Business Case

Getting approval to implement a new technology relies on the persuasiveness of the business case. A standard business case starts with the problem statement, lists some high-level requirements about what outcomes are expected, then suggests some solutions and mentions the integrations required with other systems. It ends with the business value statement and data backing up the potential of the selected technology.

Targeting the audience

Like any presentation, the key to success is to focus on who is in the audience and what is going to be persuasive to them. Not only the business management team will need to be convinced but also the finance and technical team.

“I have done a number of business cases over the course of my career, and there is a structure to them that I tend to prefer, and it is all about telling a story.”

Viral Vyas, Lead IT Business Partner at BMS


Upfront communication

But most importantly, ongoing communication with the decision makers throughout the project can help project teams to understand their expectations and concerns and address them early. The meeting at the end of the project should be more a discussion than a presentation of the project.

“It should be no surprise what you are talking about to anyone in the room, including the decision makers. They should all have heard about it before.”

Simon Cook, Research Scientist and Solution Manager at Dow Chemical



Innovative technologies can help pharmaceutical and chemical companies meet their business goals, whether through reuse of existing solutions or implementation of new technologies. Teams can build a successful business case for new technologies by involving all stakeholders from the start of the project, clearly defining KPIs, and communicating well with decision makers throughout the project.


For more information, listen to the whole discussion here in our recorded webinar.



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