Biomedical subjects

Gerd Geisslinger

Publications and source records attributed to Gerd Geisslinger.

77 records · Page 5Linked to original sources

PubMed2002

Tissue distribution of imipenem in critically ill patients.

BACKGROUND AND METHODS: Imipenem is a broad-spectrum antibiotic used mainly for serious infections in critically ill patients. Because the infection originates mostly from a certain tissue, we assessed tissue concentrations of imipenem using microdialysis in patients in intensive care with serious infections compared with healthy volunteers. Most patients were >60 years old and had renal failure; most patients also had impaired liver, heart, or lung function. RESULTS: Muscle and subcutaneous tissue concentrations in patients (maximum of 2.3 +/- 1.5 microg/mL for both muscle and subcutaneous tissue) were significantly lower than those in healthy subjects (maximum of 12.8 +/- 1.6 and 10.7 +/- 1.0 microg/mL for muscle and subcutaneous tissue). The tissue distribution rate constants for muscle and subcutaneous tissue were also significantly lower in patients (1.95 +/- 0.6 and 1.1 +/- 0.2 h(-l), respectively) than in healthy subjects (5.2 +/- 1.0 and 6.6 +/- 1.7 h(-1), respectively), meaning that tissue distribution in patients was reduced and retarded. Values for area under the plasma concentration-time curve did not significantly differ between patients and healthy subjects (37.4 +/- 5.9 microg. h/mL and 46.0 +/- 4.4 microg. h/mL, respectively,) although the elimination of imipenem in patients was prolonged (clearance, 6.3 +/- 0.8 L/h and 13.2 +/- 1.4 L/h in patients and healthy subjects, respectively). CONCLUSIONS: Our data suggest that the amount and velocity of imipenem tissue distribution in seriously ill patients is reduced compared with those values in healthy volunteers. Dose adjustments that are exclusively based on plasma concentration data may therefore be misleading and may result in potential underdosing.

Adult↗

PubMed2002

Pharmacokinetic modeling to predict morphine and morphine-6-glucuronide plasma concentrations in healthy young volunteers.

OBJECTIVE: This investigation focused on the development of a predictive model of morphine, including morphine-6-glucuronide (M6G) for healthy young volunteers after morphine administration. METHODS: Population compartmental pharmacokinetic modeling with NONMEM was applied to the plasma concentration-time data of morphine and M6G obtained from 8 healthy volunteers (4 men and 4 women; age range, 23 to 30 years) after intravenous bolus injection of 5.64 mg morphine base (7.5 mg morphine sulfate) and of 1 mg deuterium-labeled M6G. RESULTS: Two models were identified that described the plasma concentration versus time courses of morphine and M6G after administration of morphine. The model consisted of a standard 3-compartment model for morphine and a standard 2-compartment model for M6G, with input into and output from the central compartments. The formation of M6G from morphine was modeled as a fraction of morphine clearance of about 14%, which accounted for the formation of M6G, and a delay of the appearance of M6G in plasma modeled as a first-order process, with a mean metabolic transit time of 17.2 minutes. An alternative model assigned the formation of M6G among the first peripheral compartment of morphine and the central compartment of M6G. Therefore the alternative 3-compartment model of morphine had the input into the central compartment and renal excretory elimination from the central compartment, but the metabolic clearance of morphine started from the first peripheral compartment. M6G was again modeled with a standard 2-compartment model. Both models predicted morphine and M6G plasma concentrations available from an independent study with acceptable accuracy and without bias. CONCLUSIONS: Two models are provided that can predict plasma concentrations of morphine and M6G with acceptable accuracy in healthy young volunteers.

Adult↗

PubMed2002

Does the A118G polymorphism at the mu-opioid receptor gene protect against morphine-6-glucuronide toxicity?

BACKGROUND: Some, but not all, patients with renal dysfunction suffer from side effects after morphine administration because of accumulation of the active metabolite morphine-6-glucuronide (M6G). The current study aims to identify genetic causes that put patients at risk for, or protect them from, opioid side effects related to high plasma M6G. Candidate genetic causes are the single nucleotide polymorphism (SNP) A118G of the mu-opioid-receptor gene (OPRM1), which has recently been identified to result in decreased potency of M6G, and mutations in the MDR1-gene coding P-glycoprotein, of which morphine and M6G might be a substrate. METHODS: Two men, aged 87 and 65 yr, with renal failure (creatinine clearance of 6 and 9 ml/min) received 30 mg/day oral morphine for pain treatment. Both patients had sufficient analgesia from morphine. However, while one patient tolerated morphine well despite high plasma M6G of 1735 nM, in the patient with M6G plasma concentrations of 941 nM it caused severe sleepiness and drowsiness. Patients were genotyped for known SNPs of the OPRM1 and MDR1 genes. RESULTS: The patient who tolerated morphine well despite high plasma M6G was a homozygous carrier of the mutated G118 allele of the mu-opioid-receptor gene, which has been previously related to decreased M6G potency. In contrast, the patient who suffered from side effects was "wild-type" for this mutation. No other differences were found between the OPRM1 and MDR1 genes. CONCLUSIONS: The authors hypothesize that the A118G single nucleotide polymorphism of the mu-opioid-receptor is among the protective factors against M6G-related opioid toxicity. The observation encourages the search for pharmacogenetic reasons that cause interindividual variability of the clinical effects of morphine.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

PubMed2002

The polymorphism A118G of the human mu-opioid receptor gene decreases the pupil constrictory effect of morphine-6-glucuronide but not that of morphine.

Large individual differences in the clinical response to morphine therapy have been known for a long time by clinicians. The recent advances in genomic research encourage the search for pharmacogenetic causes of that variability. As a measure of central opioid effects, pupil diameters were assessed every 20 min for 18 h after administration of morphine or its active metabolite morphine-6-glucuronide (M6G) in a two-way crossover study. The opioid effects were compared between six subjects with a single-nucleotide polymorphism (SNP) A118G in the mu-opioid receptor gene (five heterozygous, one homozygous) and six control subjects. Non-parametric pharmacokinetic-pharmacodynamic modelling was employed to identify the influence of the A118G SNP on the concentration-response relationship of M6G and morphine, which was described by a sigmoid Emax model. As a measure of potency, the EC50 of the pupil constrictory effects of M6G was 714 +/- 197 nmol/l in wild-type and 1475 +/- 424 nmol/l in heterozygous carriers of the A118G SNP. In the homozygous carrier of the SNP, it had an EC50 of 3140 nmol/l. In addition, the dose-response relationship was flatter in the A118G carriers than in control subjects (shape factor of the sigmoid Emax model: gamma = 3.3 +/- 1.2, 1.7 +/- 0.5 and 1.6 for wild-type, heterozygous and the homozygous A118G carriers, respectively). In contrast, the concentration-response relationship of morphine was not affected by this specific SNP. The A118G SNP in the mu-receptor gene significantly reduces the potency of M6G in humans.

Adult↗

PubMed2002

Drug interactions with patient-controlled analgesia.

Patient-controlled analgesia (PCA) has become standard procedure in the clinical treatment of pain. Its widespread use in patients with all kinds of diseases opens a variety of possible interactions between analgesics used for PCA and other drugs that might be administered concomitantly to the patient. Many of these drug interactions are of little clinical importance. However, some drug interactions have been reported to result in serious clinical problems. Drug interactions can either predominantly affect the pharmacokinetics or pharmacodynamics of the drug. Most important pharmacokinetic drug interactions occur at the level of drug metabolism or protein binding. Acceleration of methadone metabolism caused by cytochrome P450 (CYP) 3A4 induction by antiretroviral drugs or rifampicin (rifampin) has caused methadone withdrawal symptoms. Lack of morphine formation from codeine as a result of CYP2D6 inhibition by quinidine results in an almost complete loss of the analgesic effects of codeine. Alterations of methadone protein binding caused by an inhibition of alpha1-acid glycoprotein synthesis by alkylating substances are another possibility for predominantly pharmacokinetically based drug interactions during PCA. Furthermore, inhibition of P-glycoprotein by anticancer drugs could result in altered transmembrane transport of morphine, methadone or fentanyl, although this has not been shown to be of clinical relevance. Synergistic effects of systemically administered opioids with spinally or topically delivered opioids or anaesthetics have been reported frequently. The same is true for the opioid-sparing effects of coadministered non-opioid analgesics. Antidepressants, anticonvulsants or alpha2-adrenoreceptor agonists have also been shown to exert additive analgesic effects when administered together with an opioid. Inconsistent findings, however, are reported regarding the treatment of patients with opioid-induced nausea and sedation, since coadministration of antiemetics either increased or decreased the respective adverse effects or revealed additional unwanted drug effects.

Analgesia, Patient-Controlled↗