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Giuseppe Palermo

Researcher at Hoffmann-La Roche

Publications -  14
Citations -  303

Giuseppe Palermo is an academic researcher from Hoffmann-La Roche. The author has contributed to research in topics: Chronic lymphocytic leukemia & Leukemia. The author has an hindex of 7, co-authored 13 publications receiving 219 citations.

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Model-Based dose escalation Designs in R with crmPack

TL;DR: The R package crmPack provides a simple and unified object-oriented framework for model-based dose escalation designs that enables the standard use of such designs, while being able to flexibly adapt and extend them.
Journal ArticleDOI

Gene expression of INPP5F as an independent prognostic marker in fludarabine-based therapy of chronic lymphocytic leukemia

TL;DR: Inositol polyphosphate-5-phosphatase F (INPP5F) is identified as a prognostic factor for progression-free survival and overall survival and may serve as a novel, easy-to-assess future prognostic biomarker for fludarabine-based therapy in CLL.
Proceedings ArticleDOI

F23 Validity, reliability, ability to detect change and meaningful within-patient change of the CUHDRS

TL;DR: Strong evidence of test-retest reliability, known-groups validity and ability to detect change was demonstrated and cUHDRS is valid, reliable and able to detects change in patients with early manifest HD.
Journal ArticleDOI

Results and evaluation of a first-in-human study of RG7342, an mGlu5 positive allosteric modulator, utilizing Bayesian adaptive methods.

TL;DR: This first‐in‐human study evaluated the safety and tolerability, pharmacokinetics and pharmacodynamics, and maximum tolerated dose (MTD) of single ascending oral doses of RG7342, a positive allosteric modulator of the metabotropic glutamate receptor 5 (mGlu5) for the treatment of schizophrenia, in healthy male subjects.
Journal ArticleDOI

Ranking the Predictive Power of Clinical and Biological Features Associated With Disease Progression in Huntington's Disease.

TL;DR: In this paper, a random forest regression model was trained to predict change of clinical outcomes based on the variables, which were ranked based on their contribution to the prediction, and the highest-ranked variables included novel predictors of progression, being accompanied at clinical visit, cognitive impairment, age at diagnosis and tetrabenazine or antipsychotics use.