Despite every effort to keep scientific research and science-related processes objective, completely removing bias is a difficult task. Chris Jewell, PhD, CSO at Cartesian Therapeutics, suggests one solution: “investing in advanced tools and [scientifically] diverse teams.”
Recently, Jewell and his colleagues wrote about the benefits of unbiased teams and tools in biotechnology. As these scientists pointed out: “Research is shaped by bias at multiple stages of the scientific method, spanning researchers and their techniques.” Nonetheless, the researchers noted that bioengineering “is inherently interdisciplinary, and therefore uniquely positioned to set the bar for unbiased team and technical strategies.”
By forming diverse teams to work on projects, Jewell and his colleagues believe, work is less likely to suffer from any individual’s biases. Moreover, they note that more diverse teams produce more innovative outcomes.
For examples of unbiased tools, the scientists mentioned running high-throughput assays that measure more than one analyte, such as genes and proteins or even metabolites. “A high number of analytes leads to a corresponding increase in data dimensionality, thus decreasing bias towards a specific analyte or biological outcome,” Jewell and his colleagues explain.
Companies can also create new technologies or improve existing ones by building diverse teams, often through collaborations. As one example, Teknova and Sartorius BIA Separations recently announced that they would work together on the purification of adeno-associated viruses (AAVs) in the development of gene therapies.
“Our collaboration demonstrates the importance of integrating buffer formulations with purification platforms,” says Bella Neufeld, PhD, director of research and development at Teknova. “Now, gene-therapy developers can quickly identify their optimal set of reagents for high recovery and purity of AAV, potentially saving months of development time.”
Such advances require investment, but the results justify the input. “Implementing strategies and workflows to develop unbiased teams and tools will elevate bioengineering, both in innovation and impact,” Jewell’s team notes. “Just as in nature, this cross-pollination requires action and time investment from investigators in both team building and experimental design.”
Although scientific teams and their tools will always include some sort of bias, it can be reduced in part through investing in a broader mix of people using a wider range of technologies. In fact, Jewell encourages more investment all around. Getting more from biotechnology and bioprocessing, he emphasizes, will “require additional investment of R&D resources across academics and industry.”
