Erman Sözüdoğru

In this chapter we show how pharmacological researchers manage uncertainty when using high-throughput screening (HTS) techniques. HTS allows researchers to rapidly survey the activities of large numbers of chemical compounds against a biological target. However, not all molecules that show promising biological activity during screening will be suitable for clinical use. Researchers use the concept of druglikeness to manage this uncertainty about whether a biologically active molecule will be suitable for pharmacological use. We introduce our approach in Sect. 7.1, during which we argue that the methodological choices we discuss are predicated on epistemic assumptions. We then give a brief overview of drug discovery in Sect. 7.2, and introduce HTS in more detail in Sect. 7.3. Section 7.4 then introduces druglikeness as an epistemic strategy for managing uncertainty, before discussing one of the heuristic tools, known as the rule of five, that is used by pharmacologists to reduce uncertainty about druglikeness. We conclude this chapter in more philosophical territory by considering druglikeness as a kind of extrapolation. Here, we argue that druglikeness does not seem to invoke biological mechanisms, but instead exploits the chemical capacities of molecules. The aim of this exploration is to provide a normative account of the role(s) played by values and philosophical assumptions in employing different epistemic and methodological strategies in scientific practice.

This chapter presents an active definition of uncertainty, focusing on the source and nature of the uncertainties in medical practice. This definition moves away from the common notion that equates uncertainty with the gaps in our knowledge. I argue that we must understand it as the subjective experience of the gaps in our knowledge. An important part of this experience is the awareness that our future actions are underdetermined by our current state of knowledge and that we need further judgements to determine the best course of action. The active definition of uncertainty highlights the complex nature of the judgements medical practitioners and researchers must make to resolve uncertainty.

Deciding which types of activities require an ethics review is a critical component of research regulation. Reviews conducted by research ethics committees consider the rights and safety of potential research participants, and occur as part of a wider set of governance reviews. However, to save time and resources, projects that do not raise ethical issues, or have ethical issues dealt with through other processes, are defined as out of scope for research ethics review by often being labelled as quality improvement, clinical service evaluation, audit or similar. Here we argue that the problem of identifying projects that need to be reviewed by a research ethics committee is distinct from attempts to define research more generally, and the two contexts must not be confused. We describe a pragmatic, heuristic, solution developed by the authors working with three UK government agencies, with the goal of clarifying which projects/studies require a research ethics review. Alongside applying to UK research, our approach will be of interest to international regulators and researchers when considering the wider implications as to where ethics accountability sits for different types of research-related activities.

Increased pollution, obesity rates, or the COVID-19 pandemic are only a few examples of the numerous intertwined health-environmental challenges humanity is facing. The severity of these challenges strongly suggests that research in these fields is failing to generate evidence to support decisions and actions that can help address, mitigate or adapt to them. In this article, we look into some of the underlying assumptions underpinning mainstream research in the health and in the environmental sciences; specifically, we focus on the separation between knowledge and action, mechanistic worldviews, and value-neutrality of research. We show that these assumptions underpin what we call a modernist evidence regime that is embedded in certain socio-cultural contexts. When these assumptions are at work in empirical research, interconnected health-environmental challenges cannot be appropriately addressed. We suggest, instead, that to do so we need to move towards a radically pluralist evidence regime. Such a regime sees knowledge and action as inextricably entangled, is based on a complexity-based understanding of the world, embraces the non-neutrality of research, and makes space for multiple methodological approaches.