PubMed HealthSearch

PubMed · 8211213

Optimizing high-dose therapy using pharmacokinetic principles.

Abstract

The oncologic literature of the past decade contains numerous articles supporting the concept of "dose intensity." The hypothesis that greater intensity of effective drug therapy can result in higher cure rates is supported by the results obtained in bone marrow transplantation for leukemia, lymphoma, and, possibly, breast carcinoma. Stem cell infusion overcomes the first level of the dose-limiting toxicities, ie, bone marrow suppression. This predictable toxicity develops in all patients. Second organ toxicities, such as renal, hepatic, or cardiopulmonary toxicity, occur in a less predictable manner. This variation in individual patient tolerance may be related to wide variations in drug concentration between patients while receiving the same dose. This interpatient variability has been well described for many oncologic agents, but is not unique to oncologic therapy. Important but incompletely defined relationships of importance to high-dose therapy include (1) the relationship of drug dose to concentration within patient groups and for the individual patient and (2) the relationship of drug concentration, or other related parameter such as area under the concentration versus time curve, to toxicity and outcome. Assuming such relationships can be defined, the value of using improved methods to select drug doses for an individual patient to achieve therapeutic goals needs to be explored. The purpose is to optimize therapy. In the bone marrow transplantation setting, the ideal is to provide the greatest drug exposure without undo risk of life-threatening second organ toxicity. To solve these problems, we need models that predict and allow us to control therapy in a much more precise manner than is currently possible. This review examines the concept of dose intensity, defines this concept in terms of plasma drug concentrations, and reviews methods that can aid the control of therapy in the individual patient. The potential importance of this methodology to the individual patient is discussed.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

P E Zorsky, J B Perkins. 1993. Optimizing high-dose therapy using pharmacokinetic principles.. https://pubmed.ncbi.nlm.nih.gov/8211213/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Deep generative neural network for accurate drug response imputation.

Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study, we develop a deep variational autoencoder (VAE) model to compress thousands of genes into latent vectors in a low-dimensional space. We then demonstrate that these encoded vectors could accurately impute drug response, outperform standard signature-gene based approaches, and appropriately control the overfitting problem. We apply rigorous quality assessment and validation, including assessing the impact of cell line lineage, cross-validation, cross-panel evaluation, and application in independent clinical data sets, to warrant the accuracy of the imputed drug response in both cell lines and cancer samples. Specifically, the expression-regulated component (EReX) of the observed drug response achieves high correlation across panels. Using the well-trained models, we impute drug response of The Cancer Genome Atlas data and investigate the features and signatures associated with the imputed drug response, including cell line origins, somatic mutations and tumor mutation burdens, tumor microenvironment, and confounding factors. In summary, our deep learning method and the results are useful for the study of signatures and markers of drug response.

Antineoplastic Agents

The interaction of DNA-targeted platinum phenanthridinium complexes with DNA.

Cisplatin analogues were synthesised that consisted of platinum(II) diamine complexes tethered via a polymethylene chain ( n = 3, 5, 8 and 10) to a phenanthridinium cation. Both chloro and iodo leaving groups were examined. DNA adduct formation was quantitatively analysed using a linear amplification system with the plasmid pGEM-3Zf(+). This system utilised Taq DNA polymerase to extend from an oligonucleotide primer to the damage site. This damage site inhibited the extension of the DNA polymerase. The products were electrophoresed on a DNA sequencing gel enabling adduct formation to be determined at base pair resolution. The damage intensity at each site was determined by densitometry. The platinum phenanthridinium complexes were shown to damage DNA at shorter incubation times than cisplatin. To produce similar levels of damage, an 18 h incubation was required for cisplatin compared to 30 min for the n = 3 platinum phenanthridinium complexes; this indicates that the intercalating chromophore causes a large increase in the rate of platination. A reaction mechanism involving direct displacement of the chloride by the N-7 of guanine may account for the rate increase. These results indicate that further development of these compounds could lead to more effective cancer chemotherapeutic agents.

Antineoplastic Agents

Treatment with interferon-alpha preferentially reduces the capacity for amplification of granulocyte-macrophage progenitors (CFU-GM) from patients with chronic myeloid leukemia but spares normal CFU-GM.

The biological target for interferon (IFN)-alpha in chronic myeloid leukemia (CML) is unknown, but one possibility is that amplification of granulocyte-macrophage colony-forming cells (CFU-GM) is reduced. Replating CFU-GM colonies and observing secondary colony formation provides a measure of CFU-GM amplification. Amplification of CML, but not normal, CFU-GM in vitro was significantly inhibited by IFN-alpha (P = 0.02). In 5 out of 15 CML cases studied by fluorescence in situ hybridization, in vitro treatment with IFN-alpha increased the proportion of CFU-GM, which lacked BCR-ABL. The ability of patients' CFU-GM to amplify, and suppression of this ability by IFN-alpha, predicted responsiveness to IFN-alpha therapy in 86% of cases. Investigation of patients on treatment with IFN-alpha showed a threefold reduction in CFU-GM amplification in responders (P = 0.03) but no significant change in nonresponders (P = 0.8). We conclude that IFN-alpha preferentially suppresses amplification of CML CFU-GM to varying degrees. The differing in vitro sensitivities to IFN-alpha and growth kinetics of individual patients' cells could help differentiate those who will or will not benefit from treatment with IFN-alpha.

Antineoplastic Agents