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Pregled bibliografske jedinice broj: 1018538

Predicting the effectiveness of multi-drug cancer therapies


Tomić, Draško; Pirkić, Boris; Skala, Karolj; Kranjčević, Lado
Predicting the effectiveness of multi-drug cancer therapies // 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 / Skala, Karolj (ur.).
Opatija: IEEE, 2019. str. 375-380 doi:10.23919/mipro.2019.8757131 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), ostalo)


CROSBI ID: 1018538 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Predicting the effectiveness of multi-drug cancer therapies

Autori
Tomić, Draško ; Pirkić, Boris ; Skala, Karolj ; Kranjčević, Lado

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), ostalo

ISBN
978-953233098-4

Skup
42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019

Mjesto i datum
Opatija, Hrvatska, 20-24.05.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Cancer resistance ; Effectiveness of cancer therapy ; In silico model of cancer ; Multi-drug cancer therapies ; Personalized medicine

Sažetak
Despite the ongoing development of new targeted cancer drugs, the survival rate of patients with aggressive forms of cancer like lung and pancreatic cancer is still poor. The main reason is the ability of cancer to develop resistance against cancer drugs. One strategy to overcome this resistance is to use cancer therapies with several drugs administered at the same time. This can increase our chances to kill cancer cells before they develop resistance. In order to investigate the effectiveness of such therapies, we let the in silico model of cancer Vini to calculate the most effective 2-drug therapies against non-small cell lung (NSCLC), small cell lung cancer (SCLC), and pancreatic cancer. Vini calculated the combination of vinorelbine with paclitaxel as the most effective against NSCLC, the combination of everolimus with doxorubicin as the most effective against SCLC, and the combination of everolimus with paclitaxel as the most effective against pancreatic cancer. As the existing clinical studies confirm Vini's calculations, it is justified to let Vini search for the combined cancer therapies with even more drugs. In order to further increase their effectiveness, the next research step will be the personalization of such therapies. © 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 - Proceedings. All rights reserved.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Temeljne tehničke znanosti



POVEZANOST RADA


Ustanove:
Veterinarski fakultet, Zagreb,
Tehnički fakultet, Rijeka,
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Boris Pirkić (autor)

Avatar Url Lado Kranjčević (autor)

Avatar Url Draško Tomić (autor)

Avatar Url Karolj Skala (autor)

Citiraj ovu publikaciju

Tomić, Draško; Pirkić, Boris; Skala, Karolj; Kranjčević, Lado
Predicting the effectiveness of multi-drug cancer therapies // 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 / Skala, Karolj (ur.).
Opatija: IEEE, 2019. str. 375-380 doi:10.23919/mipro.2019.8757131 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), ostalo)
Tomić, D., Pirkić, B., Skala, K. & Kranjčević, L. (2019) Predicting the effectiveness of multi-drug cancer therapies. U: Skala, K. (ur.)42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 doi:10.23919/mipro.2019.8757131.
@article{article, editor = {Skala, K.}, year = {2019}, pages = {375-380}, DOI = {10.23919/mipro.2019.8757131}, keywords = {Cancer resistance, Effectiveness of cancer therapy, In silico model of cancer, Multi-drug cancer therapies, Personalized medicine}, doi = {10.23919/mipro.2019.8757131}, isbn = {978-953233098-4}, title = {Predicting the effectiveness of multi-drug cancer therapies}, keyword = {Cancer resistance, Effectiveness of cancer therapy, In silico model of cancer, Multi-drug cancer therapies, Personalized medicine}, publisher = {IEEE}, publisherplace = {Opatija, Hrvatska} }
@article{article, editor = {Skala, K.}, year = {2019}, pages = {375-380}, DOI = {10.23919/mipro.2019.8757131}, keywords = {Cancer resistance, Effectiveness of cancer therapy, In silico model of cancer, Multi-drug cancer therapies, Personalized medicine}, doi = {10.23919/mipro.2019.8757131}, isbn = {978-953233098-4}, title = {Predicting the effectiveness of multi-drug cancer therapies}, keyword = {Cancer resistance, Effectiveness of cancer therapy, In silico model of cancer, Multi-drug cancer therapies, Personalized medicine}, publisher = {IEEE}, publisherplace = {Opatija, Hrvatska} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Conference Proceedings Citation Index - Science (CPCI-S)


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