Your goal is to extract structured information from the user's input that matches the form described below. When extracting information please make sure it matches the type information exactly. Do not add any attributes that do not appear in the schema shown below.

```TypeScript

 { // Information on the clinical trial characteristics from the abstract
 conditions: string // The condition or disease being treated in the clinical trial
 drug_or_intervention: string // The drug or intervention used in the clinical trial
}
```


Please output the extracted information in JSON format. Do not output anything except for the extracted information. Do not add any clarifying information. Do not add any fields that are not in the schema. If the text contains attributes that do not appear in the schema, please ignore them. All output must be in JSON format and follow the schema specified above. Wrap the JSON in <json> tags.



Input:Population pharmacokinetics of ganciclovir after intravenous ganciclovir and oral valganciclovir administration in solid organ transplant patients infected with cytomegalovirus.  A population pharmacokinetics analysis was performed after intravenous ganciclovir and oral valganciclovir in solid organ transplant patients with cytomegalovirus. Patients received ganciclovir at 5 mg/kg of body weight (5 days) and then 900 mg of valganciclovir (16 days), both twice daily with dose adjustment for renal function. A total of 382 serum concentrations from days 5 and 15 were analyzed with NONMEM VI. Renal function given by creatinine clearance (CL(CR)) was the most influential covariate in CL. The final pharmacokinetic parameters were as follows: ganciclovir clearance (CL) was 7.49.(CL(CR)/57) liter/h (57 was the mean population value of CL(CR)); the central and peripheral distribution volumes were 31.9 liters and 32.0 liters, respectively; intercompartmental clearance was 10.2 liter/h; the first-order absorption rate constant was 0.895 h(-1); bioavailability was 0.825; and lag time was 0.382 h. The CL(CR) was the best predictor of CL, making dose adjustment by this covariate important to achieve the most efficacious ganciclovir exposure. Output:
{'conditions': 'Cytomegalovirus Infection', 'interventions': 'Drug: Single arm (ganciclovir and valganciclovir)'}