You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:

- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.
- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.
- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.

Please format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.

As an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:

[["artesunate", "artemether", "COMB"], ["Nifedipine", "Labetalol", "Prazosin", "POS"]]

The paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.

In your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.

paragraph: Topotecan exposure estimation in pediatric acute myeloid leukemia supported by LC-MS-based drug monitoring and pharmacokinetic analysis. Individualization of the topotecan dosing can reduce inter-patient variability, toxicity, and at the same time increases chemotherapy efficacy. Topotecan dosing based on simultaneous drug monitoring and pharmacokinetic analysis can yield more accurate and precise estimation of the topotecan systemic exposure than that attainable with the fixed dosing approach. Therefore, a combined approach could provide a tool assisting the clinicians in individualization of the topotecan dosing. The aim of the study was to estimate the topotecan exposure in pediatric patients with acute myeloid leukemia (AML) based on the plasma concentration-time data and using the pharmacokinetic analysis. The primary goal was achieve the correct estimation of the target plasma area against the topotecan concentration-time curve ( AUC ) in a 5 day course of cladribine followed by monitored topotecan in pediatric patients with recurrent/refractory AML . A sensitive and selective reversed-phase liquid chromatographic-mass spectrometry (LC-MS) assay was developed to quantify total topotecan in the human plasma samples. This method, with its lower quantification limit of 1 ng/ml, was validated over a linear range of 1-150 ng/ml. Under the proposed approach, the topotecan dosing was selected so as to achieve the final AUC value of 140±20 ng/ml h. The presented analytical and pharmacokinetic data demonstrate that the proposed approach can be a practical, useful, efficient, and accurate tool for individualizing the topotecan dosing in children with AML.

sentence: The primary goal was achieve the correct estimation of the target plasma area against the topotecan concentration-time curve ( AUC ) in a 5 day course of cladribine followed by monitored topotecan in pediatric patients with recurrent/refractory AML .
[["cladribine", "topotecan", "COMB"]]