Workshop: Drug Safety, Probabilistic Causal Assessment, and Evidence Synthesis (27-28 Jan, 2017, LMU, Munich)

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Bennett Holman
Jürgen Landes
Barbara Osimani
Roland Poellinger
David Teira


The latest regulatory amendments concerning pharmacovigilance practice made by the European Parliament and the European Council (Directive 2010/84/EU; Regulation (EU) No 1235/2010) put a special emphasis on joint efforts to develop an integrative information-based approach to pharmaceutical risk assessment. The related guidelines encourage the amalgamation of information from different sources (e.g. spontaneous case reports, literature, data-mining, pharmacoepidemiological studies, post-marketing trials, drug utilization studies, non-clinical studies, late-breaking information). Yet, the methodological bases for implementing such a policy are shaky in that causal assessment of adverse drug reactions still relies mainly on the (statistical) methods developed to test drug efficacy.

Philosophers have developed a variety of tools to address methodological and epistemological issues that arise in causal assessment in medicine. This research program interacts with the work of health professionals, methodologists, statisticians and epidemiologists. Moreover, social epistemology and decision-theoretic tools are increasingly acknowledged as useful instruments to model research dynamics, knowledge flux and evaluate funding policies. Since medical research and clinical practice are pervaded by all sorts of conflicts of interest, there is room for implementing these approaches to understand the way medical knowledge works in our social world.

This workshop aims to provide a platform allowing scholars and decision makers to focus on causal assessment for the purposes of drug safety. In particular, the following topics, among others, will be explored and investigated: limits and potential of standard methods for evidence synthesis (meta-analysis, systematic review), mixed methods, machine learning and spontaneous reporting, safety pharmacology, systems pharmacology, evidence based medicine versus pluralistic approaches to evidence evaluation, and social epistemology in pharmacology. In addition, the workshop is intended to foster novel approaches to risk management and decision making.

Date and Location

It will took place on Friday the 27th of January 2017 and Saturday the 28th of January 2017 at LMU in Munich.

Speakers, Schedule, and Further Information

Please visit the workshop’s website at for details about speakers, schedule, venue, accommodation, and travel issues:


Rani Lill Anjum and Elena Rocca

Jon Williamson slides

Felipe Romero and Jan Sprenger

Barbara Osimani slides

Jeff Aronson slides

Ralph Edwards

Mike Kelly slides

Ulrich Mannsmann

Brigitte Keller-Stanislawski slides

Beth Shaw

Stephen Senn slides

Norbert Benda

Stephen Mumford

Adam La Caze slides

Jacob Stegenga

Roland Poellinger slides

Jürgen Landes slides

Martin Posch and Franz König slides

David Teira slides

Bennett Holman






Workshop on the “History of Statistics” (22/23 March, 2016)

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LMU’s department of statistics and the MCMP are jointly organizing a two-day workshop on the history of statistics. The workshop will take place on 22 and 23 March, 2016, and we are happy to announce that Glenn Shafer has agreed to open the workshop with his talk “The invention of random variables: concept and name”.

More info can be found on the homepage of the statistics department here:

Seminar on the “Philosophy of Game-Theoretic Probability” (with Glenn Shafer)

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In March, 2016, Barbara Osimani, Jürgen Landes, and Roland Poellinger will give a seminar on the “Philosophy of Game-Theoretic Probability” (co-organized with Prof. Dr. Thomas Augustin from LMU’s department of statistics). Students of LMU Munich can sign up for this course through LMU’s LSF system online and earn ECTS credit points for participation plus essay.

The event is open to all: Anyone interested in attending Glenn Shafer’s lectures only (all or some) is invited to join us at any time.

Short Description

The game-theoretic foundation for probability, launched with a 2001 book by Vladimir Vovk and Glenn Shafer, broadens the established measure-theoretic foundation for probability. This seminar and ten guest lectures by Glenn Shafer himself will provide an elementary introduction to the game-theoretic foundation, with an emphasis on its philosophical implications and its applications to the assessment of evidence.


Tuesday, 8 March, 2016 11:30-13:00 Introduction to topics from Glenn Shafer’s work: Probability, decision/game theory, evidence, causality.
Tuesday, 15 March 11:30-13:00 Guest Lecture 1: The game-theoretic definition of probability
13:00-14:00 Lunch Break
 14:00-15:30 Guest Lecture 2: Frequentism
 15:30-15:45 Coffee Break
 15:45-16:30 Discussion and Tutorial
Wednesday, 16 March 11:30-13:00 Guest Lecture 3: Dynamic martingale testing
13:00-14:00 Lunch Break
14:00-15:30 Guest Lecture 4: How to forecast
15:30-15:45 Coffee Break
15:45-16:30 Discussion and Tutorial
Thursday, 17 March 11:30-13:00 Guest Lecture 5: Subjective probability
13:00-14:00 Lunch Break
14:00-15:30 Guest Lecture 6: Dempster’s rule of combination
15:30-15:45 Coffee Break
15:45-16:30 Discussion and Tutorial
Friday, 18 March 11:30-13:00 Guest Lecture 7: Constructive decision theory
13:00-14:00 Lunch Break
14:00-15:30 Guest Lecture 8: Causality as regularity
15:30-15:45 Coffee Break
15:45-16:30 Discussion and Tutorial
Monday, 21 March 11:30-13:00 Guest Lecture 9: Game-theoretic finance I
13:00-14:00 Lunch Break
14:00-15:30 Guest Lecture 10: Game-theoretic finance II
15:30-15:45 Coffee Break
15:45-16:30 Discussion and Tutorial
 TBA  (90 min.) Review of select problems in the philosophy of probability and final discussion
 TBA  (90 min.) Essay meeting


The seminar (in English) will take place at the statistics department, seminar room 144, Ludwigstr. 33 (1st floor).


More Info

Download the guest lecture syllabus (PDF) here, and find more info on Glenn Shafer’s person and work here.

Glenn Shafer visiting MCMP/LMU (15 March – 2 April, 2016)

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We are thrilled to announce that Glenn Shafer (Rutgers) will be visiting the MCMP and the LMU statistics department in March/April 2016! He will be involved in many activities:

  1. He will give a series of 10 lectures on the philosophy of game-theoretic probability; find more details here.
  2. We are also putting together a two-day workshop with Glenn Shafer on the history of statistics (including Munich’s tradition); find more details here.
  3. And lastly, he will be one of the keynote speakers at the Munich-Sydney-Tilburg conference on evidence, inference, and risk in late March; find more details here.

Short biography

shafer_glenn_mGlenn Shafer is Professor at the Rutgers Business School – Newark and New Brunswick. He obtained his Ph.D. in mathematical statistics in 1973 from Princeton University. During is academic life he made numerous contributions to mathematics, statistics, and finance. He is one of the founding fathers of the Dempster-Shafer-Theory, which is a mathematical framework for modeling epistemic uncertainty. Among his most recent books “Probability and Finance: It’s Only a Game!” (2001, co-authored by Vladimir Vovk) provides a foundation for probability based on game theory rather than measure theory. “Algorithmic Learning in a Random World” (2005), a joint work with Vladimir Vovk and Alex Gammerman, describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness. Glenn Shafer has research interests in a great number of fields which led to publications in journals in statistics, philosophy, history, psychology, computer science, economics, engineering, accounting, and law. For more information, visit his website.



Conference on Evidence, Inference, and Risk (31 March – 2 April, 2016)

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This 9th conference of the Munich-Sydney-Tilburg (MuST) conference series aims at gathering philosophers and scientists of the natural and social sciences in order to examine the theoretical and methodological issues involved in evidence evaluation, statistical inference and causal inference in relation to risk assessment and management in various disciplines, with a special attention to pharmacology. In particular, following questions will be on focus:

How should we collect, evaluate, and use evidence for the purpose of risk management and prevention? What methods should be adopted in causal inference for preventing harm? What kinds of scientific inferences are we allowed to draw from data-mining techniques? What are the relevant decision-theoretic dimensions involved in different kinds of risks, and what kinds of decision rules are more advisable in diverse contexts? What types of uncertainties can we identify when dealing with hazards?

These questions raise methodological concerns related to the data and tools available for risk measurement and modeling, the right kinds of interventions we should adopt in order to prevent or minimize it, and the best ways to gather, evaluate and combine different sources of knowledge. Furthermore, they are intimately connected with epistemological issues in the philosophy of science, and the foundations of statistics and probability.

Pharmacology is a particularly interesting field of investigation in these respects. Together with revolutionary successes, e.g. the discovery of penicillin, the history of pharmacology is also characterized by a series of tragic disasters (from the thalidomide to the rofecoxib case), which showcase the extreme variance of its scientific performance. Furthermore, pharmaceutical decisions are set in a complex environment where scientific uncertainty, conflicts of interests, and regulatory constraints strongly interact. The workshop intends to investigate these phenomena in light of the current methodological and philosophical debate.

Find more details on the MuST 9 conference website here.