Eliseo Papa

Director of AI engineering working on AI applied to Drug Discovery. Background in biomedical engineering, data science and clinical medicine.

Experienced in

Managing an applied research machine-learning group, fostering an inclusive culture and setting the research strategy.

Fast-paced hiring to kickstart and scale an AI team.

Technical product management in applied machine learning research and software engineering.

Machine learning, python and data engineering architecture - delivering production-grade analysis pipeline to computational biology, statistical genetics and early discovery groups.

Leading academic/industrial research collaborations, communicating across disciplines, managing multi-year scientific projects, writing funding grants, leading product decisions in a software team.

Knowledge graph completion leveraging natural language processing

Drug target identification and prioritization - Genetics, integrative and network-based approaches

Sequencing analysis - QC pipelines and statistical analysis of 16S and RNA-seq experiments

Machine learning for biomarker identification - human microbiome and immune cells subpopulations

Clinical medicine - anesthesia, genetics, general medicine

Computing

Python - pytorch, DGL, DGL-KE, numpy, vega-lite, seaborne, pandas, lxml, spacy, requests.
Cloud ops - Docker, Kubernetes, Google Cloud, Azure cloud
R - reporting packages; ggplot2, knitr, shiny.
Web development - minimal knowledge of react, JSX, MDX, dc.js Linux - Git, bash/zsh, sge/torque/pbs schedulers SQL - postgresql, sqlite3, clickhouse NoSQL - elasticsearch

Product & engineer manager in an agile team.

Contributor to open source projects: open targets, kubernetes, luigi, airflow

Work

2020 - now Director AI Engineering, AstraZeneca

• scale up effective engineering team practices to a > 50 organization
• foster customer and value oriented culture
• scale up interviewing and culture-sharing
• establish academic collaborations and set a publication strategy
• stabilizing existing innovation team and bring them to the next phase of maturity

2018 - 2020 AI & Data Science Lead, AstraZeneca

• Fast-paced hiring to kickstart and scale an AI team within R&D IT.
• Leading separate teams dedicated to:
  • using BERT language-based models in NLP to extract relationship from biomedical literature
  • build a large-scale knowledge graph with internal data
  • leverage graph ML for target identification and repurposing
  • support drug discovery decision with recommender systems.
• rewrote the interview process,
• established new ways of working
• directly contributed code to new projects.

2017 - 2018 Senior Data Scientist, Translational Advanced Analytics, Biogen

2016 - 2017 Manager, Digital Health Technology & Data Science, Biogen

Concurrent projects:

1) Advanced analytics & scientific computing

• deliver production-grade analysis pipeline to Biogen’s computational biology group, statistical genetics group and early discovery groups.
• applied deep learning approaches on >22 million records from MEDLINE to suggest new scientific hypothesis.

1) Open Targets liaison

• leverage large scale human data sets with the goal of identify and prioritize new drug targets.
• Manage and influence Open Targets scientific program, working in partnership with the Wellcome Trust Sanger Institute, the European Bioinformatics Institute, and GSK.
• routinely represent Biogen externally, including speaking invitations at informatics and scientific venues.

1) Development of the Open Targets Platform

• team lead, responsible to plan and manage the work of 2 Biogen and 4 EBI engineers including weekly planning and engineering duties.
• manage the long-range planning and decision-making, including creating and owning the platform roadmap, and making sure the team adopts the tool and process.

1) Biogen’s principal liaison for the and Genomics England discovery forum

• Participated and contributed to the Genomics England GENE consortium together with VPs and Directors from AZ, GSK, Takeda, Abbvie, Alexion and others.

2015 - 2016 ML Analyst, OpenBiome / Finch Therapeutics Cambridge,MA (remote)

• Statistical analysis of microbiome communities during fecal transplant delivery by capsule
• Project consulting for large pharmaceutical to analyze prevalence of drug resistant genes in the general population
• Retrospective analysis of Phase 2b trial results and additional microbiome sequencing to measure efficacy

2014 - 2016 Chief Scientist, Klappo/um.ai, London,UK

• Building a recommendations engine to craft context-aware suggestions for every meal.
• Normalization and concept mapping used to organize natural language data related to food onto a structured ontology
• Data analysis and visualization
• Management team responsible for the business plan and investor relations
• Medical and scientific direction

Aug2013 - Dec2014 Junior doctor, Imperial College NHS Trust, London, UK

• Anesthesia
• Care of the elderly, palliative care
• Gastroenterology

2013 Theoretical System Biology group, Prof. M. Stumpf, Imperial College

• Integrating Chip-seq, RNAseq and transcriptomics data describing nitrogen stress response in e.coli
• Organized query with a relational db, structured ontology and visualization
• Bayesian model selection of potential e.coli nitrogen stress pathways

May 2012 - Dec 2012 Consultant, SERES Health, Cambridge, MA

• Selection and fitness prediction of synthetic microbial communities intended for therapeutic transplantation using unsupervised/supervised learning.
• Provided strategic input and scientific advice.

2009 - 2012 Alm Laboratory for Microbiology, Prof. Eric J. Alm, MIT

• Supervised classification of microbiome samples from pediatric IBD patients
• Feature extraction using ecological and phylogenetic information
• Quality control and downstream analysis of Human Microbiome Project sequencing pipeline

2009 Founder, Enumeral biomedical, Cambridge, MA

• MIT $100K Entrepeneurship competition semifinalist
• Contributed to the development of the microfluidic platform at the core of the company intellectual property

2006 - 2009 Laboratory of Hidde L. Ploegh, Whitehead Institute, MIT

• Unsupervised learning to map affinity and isotype of secreted antibodies in individual primary B cells.
• Describing immune response progression by statistical modelling of the B cell population
• Created a cluster pipeline to automate image analysis of fluorescence microscopy data

Education

2013 MBBS, Imperial College London Medicine & Surgery

2012 Ph.D, Harvard/MIT Health Science & Technology Institute Medical Engineering & Medical Physics

• Thesis: Applied machine learning for exploring immunity and the microbiome

2008 S.M., Massachusets Institute of Technology Mechanical Engineering

2005 BASc (Honors), University of Toronto Engineering Science, Biomedical Option

Publications

A list is also available on google scholar

Journals

2021 Rozemberczki, B., Bonner, S., Nikolov, A., Ughetto, M., Nilsson, S. and Papa, E., 2021. A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Synergy, and Drug-Drug Interaction Prediction. arXiv preprint arXiv:2111.02916.

2021 Rozemberczki, B., Gogleva, A., Nilsson, S., Edwards, G., Nikolov, A., & Papa, E. (2021). MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy. arXiv preprint arXiv:2110.15087.

2021 Gogleva, A., papa, E., Jansson, E., & De Baets, G. (2021, September). Drug Discovery as a Recommendation Problem: Challenges and Complexities in Biological Decisions. In Fifteenth ACM Conference on Recommender Systems (pp. 548-550).

2021 Mountjoy E, Schmidt EM, Carmona M, et al. An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci. Nat Genet. 2021;53(11):1527-1533. doi:10.1038/s41588-021-00945-5

2021 Gogleva, A., Polychronopoulos, D., Pfeifer, M., Poroshin, V., Ughetto, M., Sidders, B., Ahdesmäki, M., McDermott, U., Papa, E., & Bulusu, K.C. (2021). Knowledge Graph-based Recommendation Framework Identifies Novel Drivers of Resistance in EGFR mutant Non-small Cell Lung Cancer. bioRxiv.

2021 Ochoa, D., Hercules, A., Carmona, M., Suveges, D., Gonzalez-Uriarte, A., Malangone, C., Miranda, A., Fumis, L., Carvalho-Silva, D., Spitzer, M., Baker, J., Ferrer, J., Raies, A., Razuvayevskaya, O., Faulconbridge, A., Petsalaki, E., Mutowo, P., Machlitt-Northen, S., Peat, G., McAuley, E., Ong, C.K., Mountjoy, E., Ghoussaini, M., Pierleoni, A., Papa, E., Pignatelli, M., Koscielny, G., Karim, M., Schwartzentruber, J., Hulcoop, D.G., Dunham, I., & McDonagh, E.M. (2021). Open Targets Platform: supporting systematic drug-target identification and prioritisation. Nucleic acids research.

2021 Ghoussaini, M., Mountjoy, E., Carmona, M., Peat, G., Schmidt, E., Hercules, A., Fumis, L., Miranda, A., Carvalho-Silva, D., Buniello, A., Burdett, T., Hayhurst, J.D., Baker, J., Ferrer, J., Gonzalez-Uriarte, A., Jupp, S., Karim, M., Koscielny, G., Machlitt-Northen, S., Malangone, C., Pendlington, Z.M., Roncaglia, P., Suveges, D., Wright, D., Vrousgou, O., Papa, E., Parkinson, H., MacArthur, J.A., Todd, J., Barrett, J., Schwartzentruber, J., Hulcoop, D.G., Ochoa, D., McDonagh, E.M., & Dunham, I. (2021). Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics. Nucleic acids research.

2020 Jackson, R.J., Jansson, E., Lagerberg, A., Ford, E., Poroshin, V., Scrivener, T., Axelsson, M., Johansson, M., Franco, L.A., & Papa, E. (2020). Ablations over transformer models for biomedical relationship extraction. F1000Research, 9, 710.

2018 Carvalho-Silva, D., Pierleoni, A., Pignatelli, M., Ong, C.K., Fumis, L., Karamanis, N., Carmona, M., Faulconbridge, A., Hercules, A., McAuley, E., Miranda, A., Peat, G., Spitzer, M., Barrett, J., Hulcoop, D.G., Papa, E., Koscielny, G., & Dunham, I. (2019). Open Targets Platform: new developments and updates two years on. Nucleic Acids Research, 47, D1056 - D1065.

2017 Karamanis, N., Carvalho-Silva, D., Cham, J.A., Fumis, L., Hasan, S., Hulcoop, D.G., Koscielny, G., Maguire, M., Newell, W., Ong, C., Papa, E., Pierleoni, A., Pignatelli, M., Pundir, S., Rowland, F., Vamathevan, J., Watkins, X., Barrett, J.C., & Dunham, I. (2017). Designing an intuitive web application for drug discovery scientists. bioRxiv.

2017 Koscielny G, An P, Carvalho-Silva D, Cham JA, Fumis L, Gasparyan R, Hasan S, Karamanis N, Maguire M, Papa E, Pierleoni A, Pignatelli M, et al. Open Targets: a platform for therapeutic target identification and validation. Nucleic Acids Res. 2017 Jan 4;45(D1):D985-D994. doi: 10.1093/nar/gkw1055. PMC5210543.

2017 Fischer M, Bittar M, Papa E, Kassam Z, Smith M. Can You Cause Inflammatory Bowel Disease with Fecal Transplantation? A 31-Patient Case-Series of Fecal Transplantation Using Stool from a Donor Who Later Developed Crohn’s disease Gut Microbes 2017 Jan 19:0. doi: 10.1080/19490976.2017.1283469

2012 Papa E, Docktor M, Smillie C, Weber S, Preheim SP, Gevers D, Giannoukos G, Ciulla D, Tabbaa D, Ingram J, Schauer DB, Ward DV, Korzenik JR, Xavier RJ, Bousvaros A, Alm EJ. Non-invasive mapping of the gastrointestinal microbiota identifies children with inflammatory bowel disease. PLoS ONE 2012;7(6):e39242.

2011 White R, Miyata S, Papa E, Spooner E, Gounaris K, Selkirk M, Artavanis-Tsakonas K. Characterisation of the Trichinella spiralis deubiquitinating enzyme, TsUCH37, an evolutionarily conserved proteasome interaction partner. PLoS Negl Trop Dis. 2011 Oct;5(10):e1340.

2011 Artavanis-Tsakonas K, Kasperkovitz PV, Papa E, Cardenas ML, Khan NS, Van der Veen AG, Ploegh HL, Vyas JM. The Tetraspanin CD82 is Specifically Recruited to Fungal and Bacterial Phagosomes Prior to Acidification. Infection and Immunity 2011 79(3):1098-106\

2009 Adebola Ogunniyi A, Craig Story CM, Papa E, Guillen E, Love JC. Screening Individual Hybridomas by Microengraving to Discover Monoclonal Antibodies. Nature Protocols 2009 4(5):767-82

2009 Ronan JL, Story CM, Papa E, Love JC. Optimization of the surfaces used to capture antibodies from single hybridomas reduces the time required for microengraving. Journal of Immunological Methods 2009, 340(2):164-9\

2008 Papa E, Story CM◇, Hu CC, Ronan JL, Herlihy K, Ploegh HL, Love JC. Profiling Antibody Responses by Multiparametric Analysis of Single B Cells. PNAS 2008 105(46):17902-7

Patents

2009 Composition of an Array of Microwells with an Integrated Microfluidic System, US8569046B2

Fellowships

2010-2011 NSERC Postgraduate D Scholarship, Canada

2008-2009 Poitras pre-doctoral fellowship, MIT

2007 Martino Scholar, Harvard/MIT Health Science & Tech. Inst.

Awards

2020 Early Oncology AstraZeneca Award - driving innovation, Accelerating novel target discovery

2008 Martha Gray Prizes for Excellence in Research, Harvard/MIT Health Science & Tech. Inst.

2008 Competition Semifinalist, MIT 100k Business Plan