The commercialization of the biomedical sciences: (mis)understanding bias

Bias as an epistemic notion

Once one abandons the ideal of value-free, impartial science, the question of how to distinguish biased from legitimately value-laden science arises. To approach this "new demarcation problem", I argue that one should distinguish different uses of "bias" in a first step: a narrow sense of bias as systematic deviation from the truth, and a wider sense that covers any kind of tendency impacting scientific reasoning. Secondly, the narrow sense exemplifies an ontological notion of bias, which understands bias in terms of a deviation from an impartial ideal outcome. I propose to replace it with an epistemic notion of bias, which understands biased research as research that we have good reasons to suspect could have been (done) systematically better. From a socio-epistemic perspective, such good reasons to expect better can be found in a lack of responsiveness to conventional standards and/or critical discourse in the scientific community. In short, bias in an epistemic sense consists in a deviation, not from truth but from current best practice. While this turns bias into something that is dependent on time and context, it allows for value-laden research to be unbiased, if there are no good reasons to expect this research to be better.

What, Me Worry? Research Policy and the Open Embrace of Industry-Academic Relations

The field of research policy has conducted extensive research on partnerships between industry and academics and concluded that such collaborations are generally beneficial. Such a view stands in stark contrast to the literature in the philosophy of science which almost wholly finds such collaborations corrosive to scientific inquiry. After reviewing the respective literatures, I propose explanations for these polarized views which support the claim that both disciplines have only a partial vantage point on the effects of industry-funded science. In closing, I outline how the research agendas of each discipline might remediate their respective shortcomings.

How to Assess the Epistemic Wrongness of Sponsorship Bias? The Case of Manufactured Certainty

Although the impact of so-called “sponsorship bias” has been the subject of increased attention in the philosophy of science, what exactly constitutes its epistemic wrongness is still debated. In this paper, I will argue that neither evidential accounts nor social–epistemological accounts can fully account for the epistemic wrongness of sponsorship bias, but there are good reasons to prefer social–epistemological to evidential accounts. I will defend this claim by examining how both accounts deal with a paradigm case from medical epistemology, recently discussed in a paper by Bennett Holman. I will argue that evidential accounts cannot adequately capture cases of sponsorship bias that involve the manufacturing of certainty because of their neutrality with respect to the role of non-epistemic values in scientific practice. If my argument holds, it further highlights the importance of integrating social and ethical concerns into epistemological analysis, especially in applied contexts. One can only properly grasp sponsorship bias as an epistemological problem if one resists the methodological tendency to analyze social, ethical, and epistemological issues in isolation from each other.

New Developments and Insights in the Improvement of Mycobacterium tuberculosis Vaccines and Diagnostics Within the End TB Strategy

PURPOSE OF REVIEW

The alignment of sustainable development goals (SDGs) with the End Tuberculosis (TB) strategy provides an integrated roadmap to implement key approaches towards TB elimination. This review summarizes current social challenges for TB control, and yet, recent developments in TB diagnosis and vaccines in the context of the End TB strategy and SDGs to transform global health.

RECENT FINDINGS

Advances in non-sputum based TB biomarkers and whole genome sequencing technologies could revolutionize TB diagnostics. Moreover, synergistic novel technologies such as mRNA vaccination, nanovaccines and promising TB vaccine models are key promising developments for TB prevention and control.

SUMMARY

The End TB strategy depends on novel developments in point-of-care TB diagnostics and effective vaccines. However, despite outstanding technological developments in these fields, TB elimination will be unlikely achieved if TB social determinants are not fully addressed. Indeed, the End TB strategy and SDGs emphasize the importance of implementing sustainable universal health coverage and social protection.