Dear Colleague, The Summer School on Machine Learning in Drug Design will take place on August 20-22, 2018 in Leuven, Belgium. This Summer School will bring together the machine learning, chemoinformatics, and bioinformatics communities from academia and industry to tackle the challenges of complex data integration in drug design and discovery. The format of the event will combine multiple keynote presentations, oral contributions selected from submitted abstracts, and extensive poster sessions with ample time for discussion. We invite you to submit your abstract for oral presentation or poster by July 15, 2018 at http://mldd.esat.kuleuven.be. More information is available below and at http://mldd.esat.kuleuven.be, or by email at mldd@esat.kuleuven.be. Registration will open shortly. Best regards, Prof. Yves Moreau, University of Leuven Prof. Sepp Hochreiter, Johannes Kepler University of Linz Prof. Samuel Kaski, Aalto University SCOPE The data sets amenable to mining for drug design are rapidly expanding. This holds not only for the volume of conventional annotation of chemicals (i.e., representations of their chemical structure and their activities in a growing set of validated assays). It also goes for less conventional data sources, such as cellular microscopy or gene expression profiles of chemicals acquired at high throughput. Powerful novel machine learning methods unleashed on these massive volumes of heterogeneous and rich, but noisy and biased data, hold the promise of better and safer drugs to address unmet medical needs. To deliver on that promise, the Summer School calls on the machine learning, big data analytics, cheminformatics and bioinformatics communities to join forces and strengthen collaborative work at the interface of their disciplines. The Summer School will bring together contributors from both academia and industry to foster interdisciplinary exchange in this area where the need for expertise is growing rapidly. Contributions will cover recent advances in chemogenomics, strategies for data fusion, and machine learning. INVITED SPEAKERS Djork-Arné Clevert (Bayer) Daniel Reker (MIT) Gerard van Westen (Leiden University) Florian Nigsch (Novartis) Thomas Blaschke (AstraZeneca) Tim Becker (Harvard University) Gilles Marcou (University of Strasbourg) Val Gillet (University of Sheffield, TBC) INTENDED AUDIENCE AND FORMAT The summer school is intended for academic and industry researchers in machine learning, chemoinformatics, or bioinformatics who are either currently working at the interface between these fields or want to expand their skills to link these three areas. The summer school is also intended as a bridge between academia and industry. The format of the event will combine comprehensive invited presentations, oral contributions selected from submitted abstracts, and extensive poster sessions with ample time for discussion. ABSTRACT SUBMISSION Participants are invited to submit abstracts for oral contributions and posters by July 15, 2018. Abstracts can submitted for consideration for oral presentation (up to 1,000 words) or for consideration as poster only (up to 250 words). Abstracts selected for oral presentation will be notified by July 22, 2018. Abstracts will be available as a book of abstracts and online, but there will be no full proceedings. REGISTRATION AND FEE Early registration fee (before July 20, 2018): €150 (+ 21% VAT) = €181.5 Late registration fee (before August 13, 2018): €250 (+ 21% VAT) = €302.5 The fee covers participation to the meeting and includes coffee breaks and lunch (sandwich lunch). Registration will open shortly. VENUE The Summer School will be held at the Irish College, a beautifully restored historical building in the center of Leuven, Belgium.