Predicting Secukinumab Fast-Responder Profile in Psoriatic Patients: Advanced Application of Artificial-Neural-Networks (ANNs).

Journal: Journal of drugs in dermatology : JDD

PMID: 33346505

Abstract

BACKGROUND: Drug resistance to biologics in psoriasis therapy can occur – it may be acquired during a treatment or else present itself from the beginning. To date, no biomarkers are known that may reliably guide clinicians in predicting responsiveness to biologics. Biologics may pose a substantial economic burden. Secukinumab efficiently targets IL-17 in the treatment of psoriasis.

Authors

Giovanni Damiani

Department of Dermatology, Case Western Reserve University, Cleveland, OH 44195, USA.
Rosalynn R Z Conic
Paolo D M Pigatto
Carlo G Carrera
Chiara Franchi
Angelo Cattaneo
Piergiorgio Malagoli
Radhakrishna Uppala
Dennis Linder
Nicola L Bragazzi
Enzo Grossi

Villa Santa Maria Foundation, Tavernerio, Italy. enzo.grossi@bracco.com.

Keywords

Adult Antibodies, Monoclonal, Humanized Biological Products Biomarkers Deep Learning Drug Resistance Female Humans Injections, Subcutaneous Male Middle Aged Models, Immunological Pilot Projects Predictive Value of Tests Prognosis Prospective Studies Psoriasis Severity of Illness Index Time Factors Treatment Outcome

External Resources

View on PubMed Access via DOI PubMed (33346505)

Predicting Secukinumab Fast-Responder Profile in Psoriatic Patients: Advanced Application of Artificial-Neural-Networks (ANNs).

Abstract

Authors

Keywords

External Resources

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