Giovanna Li Petri

Researcher



Contact

Giovanna Li Petri

Researcher


[email protected]


Department of Chemical Science and Materials Technology (DSCTM)

National Research Council (CNR)

Istituto per lo Studio dei Materiali Nanostrutturati, CNR
Via U. La Malfa 153, 90146 Palermo (Italy)




Giovanna Li Petri

Researcher


[email protected]


Department of Chemical Science and Materials Technology (DSCTM)

National Research Council (CNR)

Istituto per lo Studio dei Materiali Nanostrutturati, CNR
Via U. La Malfa 153, 90146 Palermo (Italy)



To Combine or Not Combine: Drug Interactions and Tools for Their Analysis. Reflections from the EORTC-PAMM Course on Preclinical and Early-phase Clinical Pharmacology


Journal article


B. El Hassouni, G. Mantini, G. Li Petri, M. Capula, L. Boyd, H. N. W. Weinstein, A. Vallés-Martí, M. Kouwenhoven, E. Giovannetti, B. Westerman, G. Peters
Anticancer Research, 2019

Semantic Scholar DOI PubMed
Cite

Cite

APA   Click to copy
Hassouni, B. E., Mantini, G., Petri, G. L., Capula, M., Boyd, L., Weinstein, H. N. W., … Peters, G. (2019). To Combine or Not Combine: Drug Interactions and Tools for Their Analysis. Reflections from the EORTC-PAMM Course on Preclinical and Early-phase Clinical Pharmacology. Anticancer Research.


Chicago/Turabian   Click to copy
Hassouni, B. El, G. Mantini, G. Li Petri, M. Capula, L. Boyd, H. N. W. Weinstein, A. Vallés-Martí, et al. “To Combine or Not Combine: Drug Interactions and Tools for Their Analysis. Reflections from the EORTC-PAMM Course on Preclinical and Early-Phase Clinical Pharmacology.” Anticancer Research (2019).


MLA   Click to copy
Hassouni, B. El, et al. “To Combine or Not Combine: Drug Interactions and Tools for Their Analysis. Reflections from the EORTC-PAMM Course on Preclinical and Early-Phase Clinical Pharmacology.” Anticancer Research, 2019.


BibTeX   Click to copy

@article{b2019a,
  title = {To Combine or Not Combine: Drug Interactions and Tools for Their Analysis. Reflections from the EORTC-PAMM Course on Preclinical and Early-phase Clinical Pharmacology},
  year = {2019},
  journal = {Anticancer Research},
  author = {Hassouni, B. El and Mantini, G. and Petri, G. Li and Capula, M. and Boyd, L. and Weinstein, H. N. W. and Vallés-Martí, A. and Kouwenhoven, M. and Giovannetti, E. and Westerman, B. and Peters, G.}
}

Abstract

Combination therapies are used in the clinic to achieve cure, better efficacy and to circumvent resistant disease in patients. Initial assessment of the effect of such combinations, usually of two agents, is frequently performed using in vitro assays. In this review, we give a short summary of the types of analyses that were presented during the Preclinical and Early-phase Clinical Pharmacology Course of the Pharmacology and Molecular Mechanisms Group, European Organization for Research and Treatment on Cancer, that can be used to determine the efficacy of drug combinations. The effect of a combination treatment can be calculated using mathematical equations based on either the Loewe additivity or Bliss independence model, or a combination of both, such as Chou and Talalay's median-drug effect model. Interactions can be additive, synergistic (more than additive), or antagonistic (less than additive). Software packages CalcuSyn (also available as CompuSyn) and Combenefit are designed to calculate the extent of the combined effects. Interestingly, the application of machine-learning methods in the prediction of combination treatments, which can include pharmacogenomic, genetic, metabolomic and proteomic profiles, might contribute to further refinement of combination regimens. However, more research is needed to apply appropriate rules of machine learning methods to ensure correct predictive models.



Tools
Translate to