Francesco Pappalardo

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Full Professor

Università degli Studi di Napoli Federico II

Italy

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About

Francesco Pappalardo is a Full Professor at Università degli Studi di Catania, Italy. His research areas include bioinformatics, artificial intelligence in drug and food safety, and innovative modeling techniques for predicting health outcomes. His recent work focuses on developing protocols for allergy forecasting, in silico models for tuberculosis treatment, and bioinformatics analyses related to COVID-19 and vaccine efficacy.

Recent Grants

Grant: Close

In Silico World: Lowering barriers to ubiquitous adoption of In Silico Trials

Open Date: 2021-01-01

Close Date: 2024-12-31

Grant: Close

Identification of the Molecular Mechanisms of non-response to Treatments, Relapses and Remission in Autoimmune, Inflammatory, and Allergic Conditions

Open Date: 2019-09-01

Close Date: 2026-08-31

Grant: Close

In Silico Trial for Tuberculosis Vaccine Development

Open Date: 2018-02-01

Close Date: 2022-07-31

Grant: Close

ImmunoGrid - The European virtual human immune system project

Open Date: 2006-02-01

Close Date: 2009-01-31

Articles (16)

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2024

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2021

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2021

Collaborators (8)

Sebastiano Battiato

Full Professor

University of Catania

ITALY

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Pedro A Reche

Professor (Catedratico de Universidad)

Universidad Complutense de Madrid Facultad de Medicina

SPAIN

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Blanca Rodriguez

Professor of Computational Medicine, Research & Innovation, Advisor & Consultant, Training & Coaching

University of Oxford

UNITED KINGDOM

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Jeff Barrett

Chief Science Officer

UNITED KINGDOM

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Yazan Masannat

University of Aberdeen

UNITED KINGDOM

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Oscar Della Pasqua

UNITED KINGDOM

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Giuseppe Catanuto

Università Federico II

ITALY

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Pieter Colin

Associate professor

Universitair Medisch Centrum Utrecht

NETHERLANDS

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Francesco Pappalardo

Research Interests

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About

Recent Grants

Articles (16)

Pioneering bioinformatics with agent-based modelling: an innovative protocol to accurately forecast skin or respiratory allergic reactions to chemical sensitizers

Boosting multiple sclerosis lesion segmentation through attention mechanism

Moving Toward a Question‐Centric Approach for Regulatory Decision Making in the Context of Drug Assessment

A Credibility Assessment Plan for an In Silico Model that Predicts the Dose–Response Relationship of New Tuberculosis Treatments

Moving forward through the in silico modeling of multiple sclerosis: Treatment layer implementation and validation

Natural Language Processing to Extract Meaningful Information from a Corpus of Written Knowledge in Breast Cancer

Artificial intelligence and real-world data for drug and food safety – A regulatory science perspective

Beyond the state of the art of reverse vaccinology: predicting vaccine efficacy with the universal immune system simulator for influenza

Computational identification of differentially-expressed genes as suggested novel COVID-19 biomarkers: A bioinformatics analysis of expression profiles

Toward A Regulatory Pathway for the Use of in Silico Trials in the CE Marking of Medical Devices

Text mining and word embedding for classification of decision making variables in breast cancer surgery

A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets

Computational modelling and simulation for immunotoxicity prediction induced by skin sensitisers

How can we accelerate COVID-19 vaccine discovery?

Immune-checkpoint inhibitors from cancer to COVID-19: A promising avenue for the treatment of patients with COVID-19 (Review)

In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products

Collaborators (8)

Sebastiano Battiato

Pedro A Reche

Blanca Rodriguez

Jeff Barrett

Yazan Masannat

Oscar Della Pasqua

Giuseppe Catanuto

Pieter Colin

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