title: A physiologically based pharmacokinetic (PBPK) approach to evaluate pharmacokinetics in patients with cancer.
abstract: Potential differences in pharmacokinetics (PK) between healthy subjects and patients with cancer were investigated using a physiologically based pharmacokinetic approach integrating demographic and physiological data from patients with cancer. Demographic data such as age, sex and body weight, and clinical laboratory measurements such as albumin, alpha-1 acid glycoprotein (AAG) and hematocrit were collected in ~2500 patients with cancer. A custom oncology population profile was built using the observed relationships among demographic variables and laboratory measurements in Simcyp® software, a population based ADME simulator. Patients with cancer were older compared with the age distribution in a built-in healthy volunteer profile in Simcyp. Hematocrit and albumin levels were lower and AAG levels were higher in patients with cancer. The custom population profile was used to investigate the disease effect on the pharmacokinetics of two probe substrates, saquinavir and midazolam. Higher saquinavir exposure was predicted in patients relative to healthy subjects, which was explained by the altered drug binding due to elevated AAG levels in patients with cancer. Consistent with historical clinical data, similar midazolam exposure was predicted in patients and healthy subjects, supporting the hypothesis that the CYP3A activity is not altered in patients with cancer. These results suggest that the custom oncology population profile is a promising tool for the prediction of PK in patients with cancer. Further evaluation and extension of this population profile with more compounds and more data will be needed.
authors.affiliation: Department of Clinical Pharmacology, Genentech, 1 DNA Way, South San Francisco, CA 94080, USA.
authors.forename: Sravanthi
authors.initials: S
authors.lastname: Cheeti
authors.forename: Nageshwar R
authors.initials: NR
authors.lastname: Budha
authors.forename: Sharmila
authors.initials: S
authors.lastname: Rajan
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Dresser
authors.forename: Jin Y
authors.initials: JY
authors.lastname: Jin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014151:Anti-Anxiety Agents / Q000493:pharmacokinetics; D015992:Body Mass Index; D049628:Body Size; D001835:Body Weight; D005260:Female; D017320:HIV Protease Inhibitors / Q000493:pharmacokinetics; D006400:Hematocrit; D006801:Humans; D008297:Male; D008874:Midazolam / Q000493:pharmacokinetics*; D008875:Middle Aged; D008954:Models, Biological; D009369:Neoplasms / Q000378:metabolism*; D009961:Orosomucoid / Q000032:analysis; D019258:Saquinavir / Q000493:pharmacokinetics*; D012709:Serum Albumin / Q000032:analysis; D055815:Young Adult
chemical_list: D014151:Anti-Anxiety Agents; D017320:HIV Protease Inhibitors; D009961:Orosomucoid; D012709:Serum Albumin; D019258:Saquinavir; D008874:Midazolam