CFP: Workshop on Machine Learning for Pharma and Healthcare Applications (PharML) - Deadline June 12, 2026

[Damian Roqueiro]

PharML @ ECML-PKDD

We are thrilled to invite researchers, data scientists, and innovators from both academia and industry to share their research and practical experiences at PharML. The workshop will be held alongside the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) in the historic city of Naples, Italy.

The Core Focus

We are looking for contributions that explore:

• Cutting-Edge Applications: Novel machine learning methods tailored for pharmaceutical discovery, clinical development, and healthcare settings.

• Translational Insights: How algorithmic innovations are actively optimizing pipeline efficiency and patient outcomes.

• Cross-Sector Collaboration: Research that fosters robust dialogue and synergy between industrial practitioners and academic pioneers.

This upcoming event marks the 6th iteration of PharML at ECML-PKDD. Building on a strong legacy of innovation from our past meetings (2020, 2021, 2022, 2023, and 2025), we continue to cultivate a community dedicated to solving the most complex challenges in medicine.

Join us in Naples as we push the boundaries of computational discovery, transform complex biomedical data into actionable therapeutics, and shape the future of global healthcare.

Topics of Interest

• Large Language Models and Transformers for Pharma
  • Scientific knowledge extraction
  • Assisted indication selection
  • Assisted Medical Writing
  • Therapeutic antibody and protein representations
  • Single cell transcriptome representations
• Learning on Graphs
  • Node and link prediction on molecular graphs
  • Modelling dynamic graphs
  • Biological pathway mining for cancer biomarker discovery
  • Representing patients and molecules as graphs
• Causal inference and learning
  • Predicting the impact of interventions and discovering causal relationships from observational data.
• Machine learning for survival analysis
  • Methods for learning from time-to-event data to build prognostic or treatment-predictive models.
• Multimodal and data fusion
  • Leveraging multiple modalities including images, molecular data, text, and sensor data.
• Applied machine-learning
  • Drug Design and Discovery
  • Translational Medicine
  • Earlier Diagnosis and Differential Diagnosis
  • Personalized Healthcare and Precision Medicine
  • Patient Safety, Pharmacovigilance, and Toxicity Prediction
  • Patient Monitoring and Diagnostic Surveillance
  • Medical Devices and Digital Endpoints
  • Clinical Decision Support
  • Cluster Analysis of Electronic Health Records
  • Medical Image Processing
  • Electrogram Biosignal Processing

Important dates

• Submission Deadline: June 12, 2026 (AoE)
• Notification: June 19, 2026
• Camera-read Submission: July 10, 2026
• Workshop date: September 7, 2026 (morning session)

Paper submission guidelines
We invite authors to submit their work in either an abstract or extended format.

• Research abstracts: describe preliminary results and are meant to foster discussion of emerging topics. Maximum of 6 pages.
• Long papers: present mature work, published or unpublished. Maximum of 16 pages.

Authors of accepted manuscripts will be notified whether their submission is selected for oral presentation or poster session.

Additional guidelines

• All manuscripts will be peer-reviewed and the review process is strictly double-blind.
• All submissions must be anonymous. Make sure the document(s) you upload does not contain names, affiliations, acknowledgements or any information that can be used to directly identify you. Replace the author information with "Anonymous".  Avoid including URLs of GitHub repositories linked to you.
• Manuscripts should be in PDF format, following the Springer Lecture Notes in Computer Science style (See link for LaTeX template).
• Submissions should be done via the Conference Management Toolkit (CMT) page (link). Follow these steps to submit your manuscript:
  • In the "Author Console"  click the "+ Create new submission" button
  • Select “[PharML] Machine Learning for Pharma and Healthcare Applications”
  • Proceed with your submission

Paper publication
The PharML workshop will partner again this year with Springer to publish the workshop proceedings (See for example, link to 2023 proceedings)

Only unpublished work or extended versions of the abstracts are eligible for publication in the workshop proceedings.

Moreover, we plan to invite the authors of all the accepted short papers to submit an extended version of their articles in a supplement of a journal dedicated to our workshop.

Important note from the Conference Organizers: accepted manuscripts at the workshop without a full registration of one of the authors or in-presence presentation will not be included in the workshop proceedings.