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A model-based clinically-relevant chemotherapy scheduling algorithm for anticancer agents

HO, Thang (2015) A model-based clinically-relevant chemotherapy scheduling algorithm for anticancer agents. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Chemotherapy is the most commonly employed method for systemic cancer treatment of
solid tumors and their metastases. The balance between cancer cell elimination and host

toxicity minimization remains a challenge for clinicians when deploying chemotherapy treatments.
Our approach explicitly incorporates treatment-induced toxicities into the schedule
design. As a case study, we synthesize administration schedules for docetaxel, a widely

used chemotherapeutic employed as a monoagent or in combination for the treatment of a
variety of cancers. The primary adverse effect of docetaxel treatment is myelosuppression,
characterized by neutropenia, a low plasma absolute neutrophil count (ANC). Through the

use of model-based systems engineering tools, this thesis provides treatment schedules for
docetaxel and its combination therapies that reduce toxic side effects and improve patient

The current algorithm employs models of tumor growth, drug pharmacokinetics, and
pharmacodynamics for both anticancer effects and toxicity, as characterized by ANC. Also
included is a toxicity-rescue therapy, with granulocyte colony stimulating factor (G-CSF)
that serves to elevate ANC. The single-agent docetaxel chemotherapy schedule minimizes
tumor volume over a multi-cycle horizon, subject to toxicity and logistical constraints imposed
by clinical practice.This single-agent chemotherapy scheduling formulation is extended to
combination chemotherapy using docetaxel-cisplatin or docetaxel-carboplatin drug pairs.

The two platinum agents display different toxicities, with cisplatin exhibiting kidney function
damage and carboplatin demonstrating the same myelosuppression effects as docetaxel.
These case studies provide two different challenges to the algorithm: (i) cisplatin scheduling significantly increases the

number of variables and constraints, thereby challenging the computational engine and formulation;
(ii) carboplatin's overlapping toxicity tests the ability of the algorithm to schedule
drugs with different mechanisms of action (they act in different phases of the cellular growth
cycle) with the same toxic side effects. The simulated results demonstrate the algorithms
flexibility, in scheduling both docetaxel and cisplatin or carboplatin treatments for effective tumor
elimination and clinically acceptable toxicties. Overall, a clinically-relevant chemotherapy
scheduling optimization algorithm is provided for designing single agent and combination
chemotherapies, when toxicity and pharmacokinetic/pharmacodynamic information is available.
Furthermore, the algorithm can be extended to patient-specfic treatment by updating
the pharmacokinetic/pharmacodynamic models as data are collected during treatment.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
HO, Thangthh29@pitt.eduTHH29
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairParker, Robertrparker@pitt.eduRPARKER
Committee MemberClermont, Gillescler@pitt.eduCLER
Committee MemberShroff, Sanjeev G.sshroff@pitt.eduSSHROFF
Committee MemberBanerjee, Ipsitaipb1@pitt.eduIPB1
Date: 28 January 2015
Date Type: Publication
Defense Date: 11 July 2014
Approval Date: 28 January 2015
Submission Date: 7 July 2014
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 225
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Chemical Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Chemotherapy, docetaxel, optimization, cisplatin, carboplatin, myelosuppression, neutropenia
Date Deposited: 28 Jan 2015 19:58
Last Modified: 15 Nov 2016 14:21


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