How design of experiments lowers costs in R&D
Research and development (R&D) in the life sciences is notoriously expensive. Estimates of the average capitalised pre-launch R&D costs for a new pharmaceutical vary from US$161 million to US$4.54 billion. The 20 pharmaceutical companies that spent the most on R&D in 2021 invested between 12.6% and 40.3% of their revenue in R&D. Making R&D cost-effective is imperative to allow companies and funding bodies to sustain biological research.
Design of experiments (DOE) is a powerful methodology that can make R&D more effective and efficient. It helps get the desired results for significantly less materials, time, and money.
DOE reduces the cost of experimentation
The costs of disposable lab supplies add up, especially with inefficient experimental designs like “one factor at a time” (OFAT) or full factorials that involve many runs. Reducing the number of runs can lead to considerable institutional savings. For example, we know one pharmaceutical company that automated high-dimensional DOE experimentation for assay development. They found that a custom D-optimal design needed six times fewer wells to reach the same conclusion as a 672-run full factorial design.
Another part of this same program aimed to reduce the cost of an expensive assay by using DOE to investigate factors that minimised expensive reagents while maintaining similar assay quality. The DOE investigation resulted in a model with two peak conditions, one of which approximately halved expensive reagent use while maintaining similar assay quality.
DOE can reduce reagent cost
Large-scale mammalian cell culture can be costly due to the large volume of cytokines and growth factors. To minimise costs, companies producing mammalian cells for consumer markets aim to reduce the use of these expensive materials. HigherSteaks, for example, reprograms animal cells into stem cells to create meat products.
However, commercial growth media is unsuitable for human consumption and can increase production costs at least 100-fold compared to livestock farming. Using a fractional factorial DOE design, HigherSteaks used DOE to screen 22 factors and profile the interactions in 320 experimental runs in just a few weeks, significantly increasing cellular yield and reducing costs by an order of magnitude.
DOE improves experiment quality
DOE experiments provide more reliable and higher-quality results than OFAT experiments. DOE can reduce errors in the system and save time exploring irrelevant options. It also provides a more comprehensive view of the experimental space, leading to more confidence in the results.
At an institutional level, DOE can promote collaboration by systematically exploring the experimental space, which reduces inconsistencies and improves the ability to combine results. This leads to better-informed new experiments and less time wasted on repeating earlier ones, saving both money and time.
DOE improves experiment robustness
DOE campaigns determine the sensitivity of a system to changes in factor levels. A robust system has smaller variability to changes than a less robust system. This is important when establishing that a process is robust to regulatory authorities. DOE can, for example, very accurately determine if temperature influences outcome.
DOE can create inherently robust processes using Quality by Design techniques. This can lead to significant cost savings compared to re-optimizing an existing process.
For example, Oxford Biomedica optimised transfection reagent mixes to improve the efficiency and robustness of in-house lentiviral vector transduction. DOE helped to plan and execute a two-iteration optimisation and robustness study of their transfection and transduction processes, resulting in up to a 10-fold increase in vector titer and an 81% reduction in variability. The approach resulted in a 32% resource saving.
The bottom line: how DOE helps
R&D is expensive, but DOE can help organisations, laboratories, and individual researchers cost-effectively answer critical biological and commercial questions. Synthace, in particular, can make R&D more efficient. With inefficient experimental designs, the costs of disposables add up quickly. Cell culture R&D is just one area set to become even more costly, with critical factors and interactions becoming more complex.
These examples show that DOE can improve R&D cost-effectiveness, although the time and resource savings depend on individual circumstances. Nonetheless, using DOE to achieve this goal is more than an aspiration, as its theoretical benefits translate into the real world.
Dr Markus Gershater, Co-Founder and Chief Scientific Officer at Synthace.