Mattia Andreoletti

Over the last decade, philosophers of science have extensively criticized the epistemic superiority of randomized controlled trials for testing safety and effectiveness of new drugs, defending instead various forms of evidential pluralism. We argue that scientific methods in regulatory decision-making cannot be assessed in epistemic terms only: there are costs involved. Drawing on the legal distinction between rules and standards, we show that drug regulation based on evidential pluralism has much higher costs than our current RCT-based system. We analyze these costs and advocate for evaluating any scheme for drug regulatory tests in terms of concrete empirical benchmarks, like the error rates of regulatory decisions.

Replicability is widely regarded as one of the defining features of science and its pursuit is one of the main postulates of meta-research, a discipline emerging in response to the replicability crisis. At the same time, replicability is typically treated with caution by philosophers of science. In this paper, we reassess the value of replicability from an epistemic perspective. We defend the orthodox view, according to which replications are always epistemically useful, against the more prudent view that claims that it is useful in very limited circumstances. Additionally, we argue that we can learn more about the original experiment and the limits of the discovered effect from replications at different levels. We hold that replicability is a crucial feature of experimental results and scientists should continue to strive to secure it.

In the last few years, the lack of a unitary notion of gene across biological sciences has troubled the philosophy of biology community. However, the debate on this concept has remained largely historical or focused on particular cases presented by the scientific empirical advancements. Moreover, in the literature there are no explicit and reasonable arguments about why a philosophical clarification of the concept of gene is needed. In our paper, we claim that a philosophical clarification of the concept of gene does not contribute to biology. Unlike the question, for example, “What is a biological function?”, we argue that the question “What is a gene?” could be answered by means of empirical research, in the sense that biologists' labour is enough to shed light on it.

The increasing success of the evidence-based policy movement is raising the demand of empirically informed decision making. As arguably any policy decision happens under conditions of uncertainty, following our best available evidence to reduce the uncertainty seems a requirement of good decision making. However, not all the uncertainty faced by decision makers can be resolved by evidence. In this paper, we build on a philosophical analysis of uncertainty to identify the boundaries of scientific advice in policy decision making. We start by introducing a distinction between empirical and non-empirical types of uncertainty, and we explore the role of two non-empirical uncertainties in the context of policy making. We argue that the authority of scientific advisors is limited to empirical uncertainty and cannot extend beyond it. While the appeal of evidence-based policy rests on a view of scientific advice as limited to empirical uncertainty, in practice there is a risk of over reliance on experts beyond the legitimate scope of their authority. We conclude by applying our framework to a real-world case of evidence-based policy, where experts have overstepped their boundaries by ignoring non-empirical types of uncertainty.

Reasoning in medicine requires the critical use of a clinical methodology whose validity must be evaluated as well as its limits. In the last decade, an increasing amount of evidence has shown severe limitations and flaws in the conduct of prognostic studies. The main reason behind this fact is that prognostic judgments are at high risk of error. In this paper we investigate the pragmatic and illocutionary aspects of different forms of linguistic acts and judgments involved in clinical practice. More specifically, we analyze the role of uncertainty with regard to ‘particular’ clinical judgments and its relation with ‘general’ evidence. Focusing on how prognostic judgments are formulated and justified, our main purpose is to highlight the explication, the structure and the limits of prognosis from a linguistic and epistemological perspective.

In the last decade, robustness has been extensively mentioned and discussed in biology as well as in the philosophy of the life sciences. Nevertheless, from both fields, someone has affirmed that this debate has resulted in more semantic confusion than in semantic clearness. Starting from this claim, we wish to offer a sort of prima facie map of the different usages of the term. In this manner we would intend to predispose a sort of “semantic platform” which could be exploited by those who wish to discuss or simply use it. We do this by starting from a core distinction between the robustness of representations, which is a philosophy of science issue, and the representations of robustness, which instead pertains to science. We illustrate our proposal with examples from biology, physics and mathematics.

Science progresses through debate and disagreement, and scientific controversies play a crucial role in the growth of scientific knowledge. However, not all controversies and disagreements are progressive in science. Sometimes, controversies can be pseudoscientific; in fact, bogus controversies, and what seem like genuine scientific disagreements, can be a distortion of science set up by non-scientific actors. Bogus controversies are detrimental to science because they can hinder scientific progress and eventually bias science-based decisions. The first goal of this paper is to elucidate the distinction between bogus and genuine scientific controversies and provide a qualitative methodology, based on the literature on expertise, for distinguishing between the two. We will illustrate six epistemic criteria for distinguishing bogus from genuine scientific debates in science and medicine. This heuristic strategy applies directly to scientific reports, and it relies mostly on the social structure of science. We will then apply the above criteria to a case study: the controversy over statins, which are widely prescribed drugs for reducing the level of cholesterol and preventing cardiovascular disease.

This Special Issue titled "Severe Uncertainty in Science, Medicine and Technology" aims to shed new light on the understanding of severe uncertainty and its multifaceted implications. The main idea of the papers of this collection is that, despite possible sophisticated statistical judgments towards future risks in science, medicine, and technology, severe forms of uncertainty still exist.While ignorance is usually assumed to be a total absence of knowledge, uncertainty often refers to the incompleteness of knowledge or information. In its extreme form, this is called "severe uncertainty" but is also known as "fundamental," "radical," "deep," "great," or "genuine" uncertainty. A common characteristic of these...

In recent years, science and technology have made great progress towards a better understanding of fundamental biological mechanisms of the diseases. Physicians, relying just on their own clinical experience, have long recognized that each patient is different from every other patient in many aspects. It is a matter of simple facts that many patients die without responding to any treatment, while others with the same disease survive. In oncology, the variability of treatment response has been a long-standing problem. Nowadays, thanks to genomics and post-genomics advancements, we have identified an indication for that individual variability: tumor heterogeneity. Each tumor has a different genomic basis...

Drugs addressing unmet medical needs can change the lives of millions. Developing and validating new drugs can, however, take many years. To streamline the assessment of new drugs, regulatory agencies have long established shortened review pathways. Among these programs, Accelerated Approval (AA) has recently come under scrutiny due to the U.S. Food and Drug Administration's decision to authorize Aducanumab, the first Alzheimer's disease drug. This decision attracted fierce criticism due to the allegedly insufficient evidence about the safety and efficacy of the drug. While considerable scholarly attention has been devoted to this case, the ethical aspects of the AA regulatory pathway have so far remained relatively unexplored. In this paper, we set out to fill this gap. We illustrate six conditions that should be met for AA to be ethically acceptable: moral solicitude, evidence, risk mitigation, impartiality, sustainability, and transparency. We discuss such conditions and suggest practical steps to implement them in regulatory and oversight processes. Taken together, our six conditions represent a benchmark for assessing the ethical validity of AA processes and decisions.

It has now been more than a year since the start of the COVID-19 pandemic. Yet, despite the colossal and unprecedented scientific effort that has been put into it, many claims are still opaque, and many issues must be solved. Among these, one deserves the attention of philosophers of science: the scientific controversy about the theories of SARS-CoV-2 transmission. In this short paper, I analyze the debate between the droplet theory and the airborne theory of viral transmission. I argue that the acceptance of the droplet theory has been due to the philosophical commitments of the dominant scientific actors to a specific theory of evidence, which has become dominant in western democracies, and to a specific set of non-epistemic values, rather than to scientific considerations alone.