Miho, Enkelejda

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Miho
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Enkelejda
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Miho, Enkelejda

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20223
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Thema: 600 - Technik, Medizin, angewandte Wissenschaften ×

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  • Vorschaubild nicht verfügbar
    Publikation
    Unconstrained generation of synthetic antibody–antigen structures to guide machine learning methodology for antibody specificity prediction
    (Nature, 19.12.2022) Robert, Philippe A.; Akbar, Rahmad; Pavlović, Milena; Widrich, Michael; Snapkov, Igor; Slabodkin, Andrei; Chernigovskaya, Maria; Scheffer, Lonneke; Smorodina, Eva; Rawat, Puneet; Mehta, Brij Bhushan; Vu, Mai Ha; Mathisen, Ingvild Frøberg; Prósz, Aurél; Abram, Krzysztof; Olar, Axel; Miho, Enkelejda; Haug, Dag Trygve Tryslew; Lund-Johansen, Fridtjof; Hochreiter, Sepp; Hobæk Haff, Ingrid; Klambauer, Günter; Sandve, Geir Kjetil; Greiff, Victor [in: Nature Computational Science]
    Machine learning (ML) is a key technology for accurate prediction of antibody–antigen binding. Two orthogonal problems hinder the application of ML to antibody-specificity prediction and the benchmarking thereof: the lack of a unified ML formalization of immunological antibody-specificity prediction problems and the unavailability of large-scale synthetic datasets to benchmark real-world relevant ML methods and dataset design. Here we developed the Absolut! software suite that enables parameter-based unconstrained generation of synthetic lattice-based three-dimensional antibody–antigen-binding structures with ground-truth access to conformational paratope, epitope and affinity. We formalized common immunological antibody-specificity prediction problems as ML tasks and confirmed that for both sequence- and structure-based tasks, accuracy-based rankings of ML methods trained on experimental data hold for ML methods trained on Absolut!-generated data. The Absolut! framework has the potential to enable real-world relevant development and benchmarking of ML strategies for biotherapeutics design.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    RWD-Cockpit. Application for quality assessment of real-world data
    (JMIR Publications, 18.10.2022) Degen, Markus; Babrak, Lmar; Smakaj, Erand; Agac, Teyfik; Asprion, Petra; Grimberg, Frank; Van der Werf, Daan; Van Ginkel, Erwin Willem; Tosoni, Deniz David; Clay, Ieuan; Brodbeck, Dominique; Natali, Eriberto; Schkommodau, Erik; Miho, Enkelejda [in: JMIR Formative Research]
    Digital technologies are transforming the health care system. A large part of information is generated as real-world data (RWD). Data from electronic health records and digital biomarkers have the potential to reveal associations between the benefits and adverse events of medicines, establish new patient-stratification principles, expose unknown disease correlations, and inform on preventive measures. The impact for health care payers and providers, the biopharmaceutical industry, and governments is massive in terms of health outcomes, quality of care, and cost. However, a framework to assess the preliminary quality of RWD is missing, thus hindering the conduct of population-based observational studies to support regulatory decision-making and real-world evidence.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Sequencing of the M protein. Toward personalized medicine in monoclonal gammopathies
    (Wiley, 23.08.2022) Cascino, Pasquale; Nevone, Alice; Piscitelli, Maggie; Scopelliti, Claudia; Girelli, Maria; Mazzini, Giulia; Caminito, Serena; Russo, Giancarlo; Milani, Paolo; Basset, Marco; Foli, Andrea; Fazio, Francesca; Casarini, Simona; Massa, Margherita; Bozzola, Margherita; Ripepi, Jessica; Sesta, Melania Antonietta; Acquafredda, Gloria; De Cicco, Marica; Moretta, Antonia; Rognoni, Paola; Milan, Enrico; Ricagno, Stefano; Lavatelli, Francesca; Petrucci, Maria Teresa; Klersy, Catherine; Merlini, Giampaolo; Palladini, Giovanni; Nuvolone, Mario; Miho, Enkelejda [in: American Journal of Hematology]
    Each patient with a monoclonal gammopathy has a unique monoclonal (M) protein, whose sequence can be used as a tumoral fingerprint to track the presence of the B cell or plasma cell (PC) clone itself. Moreover, the M protein can directly cause potentially life-threatening organ damage, which is dictated by the specific, patient's unique clonal light and/or heavy chain amino acid sequence, as in patients affected by immunoglobulin light chain (AL) amyloidosis.1 However, patients' specific M protein sequences remain mostly undefined and molecular mechanisms underlying M protein-related clinical manifestations are largely obscure.
    01A - Beitrag in wissenschaftlicher Zeitschrift