Accepted Paper:

Treatment algorithms: a new clinical tool for oncology's genomic-driven trials  

Authors:

Etienne Vignola-Gagné (McGill University)
Pascale Bourret (Aix-Marseille Université / SESSTIM)
Sylvain Besle (INSERM)

Paper short abstract:

In order to make therapeutic inferences, genomic-driven cancer clinical trials resort to treatment algorithms that establish meaningful connections between genomic, drug, and other datasets. Algorithms redefine the epistemic significance of translational processes and entities.

Paper long abstract:

We recently witnessed the emergence of clinical trials that focus on drug allocation based on genomic alterations. These trials face a major challenge: the interpretation of genomic sequencing data is a moving target, insofar as it needs to articulate four shifting reference poles: pharmaceutical drug portfolios, biopathological targets, patient populations and sequencing technologies.

Treatment algorithms, understood as predefined sets of rules for transforming sequencing and other data into evidence for therapeutic choices, are at the core of a restricted number of cutting edge trials. They act as tools that temporarily stabilize relations across the aforementioned reference poles, selecting treatment options for tumors carrying specific mutations, as detected by sequencing technologies. The analysis of how algorithms are deployed in clinical research allows us to gain a number of basic insights into the transformations introduced by precision medicine. The paper examines, in particular: (a) How algorithms manage the tension between the regulatory requirement of replication, and the clinical and scientific value of thoroughness; (b) How algorithms inflect the epistemic significance of clinical trials; and (c) How algorithms generate a new kind of experimental space by connecting heterogeneous entities.

More generally, we will show that algorithms can be understood as translational tools used to generate clinical knowledge based on genomic information. To examine this claim we resort to empirical case studies of the deployment of algorithms within four international cancer clinical trials, complemented by interviews with clinical researchers and bioinformatics specialists, and by documentary analysis of major North American and European cancer initiatives.

Panel T031
Topographies of clinical translation: charting novel sociotechnical landscapes within and around biomedical research.