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A Systems Biology Approach in Therapeutic Response Study for Different Dosing Regimens-a Modeling Study of Drug Effects on Tumor Growth using Hybrid Systems.

Li X, Qian L, Bittner ML, Dougherty ER - Cancer Inform (2012)

Bottom Line: The first one is to involve effective mathematical modeling in the drug development stage to incorporate preclinical and clinical data in order to decrease costs of drug development and increase pipeline productivity, since it is extremely expensive and difficult to get the optimal compromise of dosage and schedule through empirical testing.The second objective is to provide valuable suggestions to adjust individual drug dosing regimens to improve therapeutic effects considering most anticancer agents have wide inter-individual pharmacokinetic variability and a narrow therapeutic index.It is proved analytically that there exists an optimal drug dosage and interval administration point, and demonstrated through simulation study.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.

ABSTRACT
Motivated by the frustration of translation of research advances in the molecular and cellular biology of cancer into treatment, this study calls for cross-disciplinary efforts and proposes a methodology of incorporating drug pharmacology information into drug therapeutic response modeling using a computational systems biology approach. The objectives are two fold. The first one is to involve effective mathematical modeling in the drug development stage to incorporate preclinical and clinical data in order to decrease costs of drug development and increase pipeline productivity, since it is extremely expensive and difficult to get the optimal compromise of dosage and schedule through empirical testing. The second objective is to provide valuable suggestions to adjust individual drug dosing regimens to improve therapeutic effects considering most anticancer agents have wide inter-individual pharmacokinetic variability and a narrow therapeutic index. A dynamic hybrid systems model is proposed to study drug antitumor effect from the perspective of tumor growth dynamics, specifically the dosing and schedule of the periodic drug intake, and a drug's pharmacokinetics and pharmacodynamics information are linked together in the proposed model using a state-space approach. It is proved analytically that there exists an optimal drug dosage and interval administration point, and demonstrated through simulation study.

No MeSH data available.


Related in: MedlinePlus

The concentration level of drug under periodic drug intake. Two cases are shown: (1) large dose with longer period; (2) small dose with shorter period.
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f1-cin-11-2012-041: The concentration level of drug under periodic drug intake. Two cases are shown: (1) large dose with longer period; (2) small dose with shorter period.

Mentions: We consider a periodic drug intake scenario. One could use a detailed theoretical or empirical pharmacokinetic description of time dependent drug concentration at the site of action in a simulation study. We prefer to keep the model mathematically tractable so that we can perform a strict theoretical analysis and thereby gain insights. Thus, we assume the concentration has exponential decay. Since we are using hybrid systems, the PK model can be extended to include more complicated cases, such as the case where the drug concentration will first exponentially increase, then slowly change (equilibrium), and then exponentially decrease.63 The model used for drug intake and concentration levels is illustrated in Figure 1. We denote the period of drug intake for the two cases as τ1 and τ2, respectively. Without loss of generality, it is assumed that τ1 = Mτ2, where M > 1 is an integer. It is also assumed that u1(kτ1) = ζ1 = Mu2(lτ2) = Mζ2, where k and l are non-negative integers, and ζ1 and ζ2 are dosages in cases 1 and 2, respectively. This means that, in the long run, the patient takes the same total drug amount in both cases. It is assumed that the concentration level of the drug at the effect site follows exponential decay during each period, ie, ui(t) = ζie−λd (t−kτi), where kτi ≤ t ≤ (k + 1) τi and λd is the degradation factor. Note that Figure 1 does not show the case where there is “leftover” from the previous dosage when the patient is taking the current dosage.


A Systems Biology Approach in Therapeutic Response Study for Different Dosing Regimens-a Modeling Study of Drug Effects on Tumor Growth using Hybrid Systems.

Li X, Qian L, Bittner ML, Dougherty ER - Cancer Inform (2012)

The concentration level of drug under periodic drug intake. Two cases are shown: (1) large dose with longer period; (2) small dose with shorter period.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3298374&req=5

f1-cin-11-2012-041: The concentration level of drug under periodic drug intake. Two cases are shown: (1) large dose with longer period; (2) small dose with shorter period.
Mentions: We consider a periodic drug intake scenario. One could use a detailed theoretical or empirical pharmacokinetic description of time dependent drug concentration at the site of action in a simulation study. We prefer to keep the model mathematically tractable so that we can perform a strict theoretical analysis and thereby gain insights. Thus, we assume the concentration has exponential decay. Since we are using hybrid systems, the PK model can be extended to include more complicated cases, such as the case where the drug concentration will first exponentially increase, then slowly change (equilibrium), and then exponentially decrease.63 The model used for drug intake and concentration levels is illustrated in Figure 1. We denote the period of drug intake for the two cases as τ1 and τ2, respectively. Without loss of generality, it is assumed that τ1 = Mτ2, where M > 1 is an integer. It is also assumed that u1(kτ1) = ζ1 = Mu2(lτ2) = Mζ2, where k and l are non-negative integers, and ζ1 and ζ2 are dosages in cases 1 and 2, respectively. This means that, in the long run, the patient takes the same total drug amount in both cases. It is assumed that the concentration level of the drug at the effect site follows exponential decay during each period, ie, ui(t) = ζie−λd (t−kτi), where kτi ≤ t ≤ (k + 1) τi and λd is the degradation factor. Note that Figure 1 does not show the case where there is “leftover” from the previous dosage when the patient is taking the current dosage.

Bottom Line: The first one is to involve effective mathematical modeling in the drug development stage to incorporate preclinical and clinical data in order to decrease costs of drug development and increase pipeline productivity, since it is extremely expensive and difficult to get the optimal compromise of dosage and schedule through empirical testing.The second objective is to provide valuable suggestions to adjust individual drug dosing regimens to improve therapeutic effects considering most anticancer agents have wide inter-individual pharmacokinetic variability and a narrow therapeutic index.It is proved analytically that there exists an optimal drug dosage and interval administration point, and demonstrated through simulation study.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.

ABSTRACT
Motivated by the frustration of translation of research advances in the molecular and cellular biology of cancer into treatment, this study calls for cross-disciplinary efforts and proposes a methodology of incorporating drug pharmacology information into drug therapeutic response modeling using a computational systems biology approach. The objectives are two fold. The first one is to involve effective mathematical modeling in the drug development stage to incorporate preclinical and clinical data in order to decrease costs of drug development and increase pipeline productivity, since it is extremely expensive and difficult to get the optimal compromise of dosage and schedule through empirical testing. The second objective is to provide valuable suggestions to adjust individual drug dosing regimens to improve therapeutic effects considering most anticancer agents have wide inter-individual pharmacokinetic variability and a narrow therapeutic index. A dynamic hybrid systems model is proposed to study drug antitumor effect from the perspective of tumor growth dynamics, specifically the dosing and schedule of the periodic drug intake, and a drug's pharmacokinetics and pharmacodynamics information are linked together in the proposed model using a state-space approach. It is proved analytically that there exists an optimal drug dosage and interval administration point, and demonstrated through simulation study.

No MeSH data available.


Related in: MedlinePlus