PharmTeX: a LaTeX-Based Open-Source Platform for Automated Reporting Workflow.

Every year, the pharmaceutical industry generates a large number of scientific reports related to drug research, development, and regulatory submissions. Many of these reports are created using text processing tools such as Microsoft Word. Given the large number of figures, tables, references, and other elements, this is often a tedious task involving hours of copying and pasting and substantial efforts in quality control (QC). In the present article, we present the LaTeX-based open-source reporting platform, PharmTeX, a community-based effort to make reporting simple, reproducible, and user-friendly. The PharmTeX creators put a substantial effort into simplifying the sometimes complex elements of LaTeX into user-friendly functions that rely on advanced LaTeX and Perl code running in the background. Using this setup makes LaTeX much more accessible for users with no prior LaTeX experience. A software collection was compiled for users not wanting to manually install the required software components. The PharmTeX templates allow for inclusion of tables directly from mathematical software output as well and figures from several formats. Code listings can be included directly from source. No previous experience and only a few hours of training are required to start writing reports using PharmTeX. PharmTeX significantly reduces the time required for creating a scientific report fully compliant with regulatory and industry expectations. QC is made much simpler, since there is a direct link between analysis output and report input. PharmTeX makes available to report authors the strengths of LaTeX document processing without the need for extensive training. Graphical Abstract ᅟ.

Pregabalin effect on steady-state pharmacokinetics of carbamazepine, lamotrigine, phenobarbital, phenytoin, topiramate, valproate, and tiagabine.

By reducing neuronal excitability through selective binding to the α(2)δ subunit of voltage-dependent calcium channels, pregabalin effectively treats epilepsy, chronic pain, and anxiety disorders. To evaluate if pregabalin coadministration affects pharmacokinetics of other antiepileptic drugs, population pharmacokinetic analyses using NONMEM software were performed on data from three epilepsy trials involving seven antiepileptic drugs with pregabalin as add-on therapy. Results demonstrated that pregabalin did not alter the steady-state plasma concentrations of carbamazepine, lamotrigine, phenobarbital, phenytoin, tiagabine, topiramate, and valproate. Furthermore, the small percent change in the population estimate of antiepileptic drug plasma clearance values (-2% to +7%) suggests that pregabalin coadministration exerted no significant effect on the pharmacokinetics of these antiepileptic drugs, with the possible exception of tiagabine (+34.9%). These findings are in agreement with those of previously published reports. A further clarification study is necessary for tiagabine. In conclusion, it appears that pregabalin can be coadministered with other antiepileptic drugs without concern for significantly altering their pharmacokinetic profiles.

Population pharmacokinetics of pregabalin in healthy subjects and patients with chronic pain or partial seizures.

PURPOSE: Pregabalin, a high-affinity ligand for α2δ subunits of voltage-gated calcium channels, is a novel pharmacotherapy for chronic pain, partial seizures, and other disorders. The present study investigated the population pharmacokinetics of pregabalin following single and multiple doses in healthy volunteers and patient populations. METHODS: Using nonlinear mixed-effect modeling, 5,583 plasma pregabalin concentration-time samples from 1,723 subjects were analyzed: 2,868 samples from healthy volunteers or subjects with renal impairment (n = 123), 1,513 from patients with partial seizures (n = 626), and 1,202 from patients with chronic pain (n = 974). A one-compartment model with first-order elimination and absorption processes and absorption lag time was used. KEY FINDINGS: This pharmacostatistical model showed that: (1) pregabalin oral clearance (CL/F) was directly proportional to creatinine clearance (CLcr), but was independent of gender, race, age, female hormonal status, daily dose, and dosing regimen; (2) apparent volume of distribution was dependent on body weight and gender; (3) absorption rate was decreased when given with food; and (4) coadministration with marketed antiepileptic drugs (AEDs) had no significant effect on pregabalin CL/F. SIGNIFICANCE: Pregabalin CL/F is related to CLcr, and this relationship is similar among healthy volunteers and patients with either partial seizures or chronic pain disorders. The only factor having a clinically significant influence on steady-state plasma pregabalin concentrations is renal function.

A comparison of the pharmacokinetics and pharmacodynamics of pregabalin and gabapentin.

Pregabalin and gabapentin share a similar mechanism of action, inhibiting calcium influx and subsequent release of excitatory neurotransmitters; however, the compounds differ in their pharmacokinetic and pharmacodynamic characteristics. Gabapentin is absorbed slowly after oral administration, with maximum plasma concentrations attained within 3-4 hours. Orally administered gabapentin exhibits saturable absorption--a nonlinear (zero-order) process--making its pharmacokinetics less predictable. Plasma concentrations of gabapentin do not increase proportionally with increasing dose. In contrast, orally administered pregabalin is absorbed more rapidly, with maximum plasma concentrations attained within 1 hour. Absorption is linear (first order), with plasma concentrations increasing proportionately with increasing dose. The absolute bioavailability of gabapentin drops from 60% to 33% as the dosage increases from 900 to 3600 mg/day, while the absolute bioavailability of pregabalin remains at > or = 90% irrespective of the dosage. Both drugs can be given without regard to meals. Neither drug binds to plasma proteins. Neither drug is metabolized by nor inhibits hepatic enzymes that are responsible for the metabolism of other drugs. Both drugs are excreted renally, with elimination half-lives of approximately 6 hours. Pregabalin and gabapentin both show dose-response relationships in the treatment of postherpetic neuralgia and partial seizures. For neuropathic pain, a pregabalin dosage of 450 mg/day appears to reduce pain comparably to the predicted maximum effect of gabapentin. As an antiepileptic, pregabalin may be more effective than gabapentin, on the basis of the magnitude of the reduction in the seizure frequency. In conclusion, pregabalin appears to have some distinct pharmacokinetic advantages over gabapentin that may translate into an improved pharmacodynamic effect.

Exposure-response analyses of the effects of pregabalin in patients with fibromyalgia using daily pain scores and patient global impression of change.

Data from 4 phase 2/3 studies were pooled to characterize the exposure response of daily pregabalin (150-600 mg) in patients with fibromyalgia using self-assessed daily pain scores (PAIN) and end-of-treatment patient global impression of change (PGIC). The exposure responses of both endpoints were characterized by an Emax model using nonlinear mixed-effects modeling (NONMEM). Drug effect on PAIN relative to placebo was significant with additional maximum effect of 1.51 points on the logit scale and EC50 of 1.54 ng/mL (dose of 174 mg) and a rapid onset (half-life of 11 hours), consistent with the half-life of the drug. The decrease in PAIN with placebo occurred more slowly, reaching maximum response (1.52 points on the logit scale) after 1 month. Drug response in fibromyalgia was dependent on age and sex, with greater PAIN reduction in older patients, in addition to the effect of creatinine clearance, and in females. For PGIC, administration of pregabalin resulted in an increase in the proportion of patients reporting improvement with an ED50 of 228 mg. The analyses support the recommended dose of pregabalin in patients with fibromyalgia of 300 to 450 mg/d.

Mixed effects modeling of weight change associated with placebo and pregabalin administration.

OBJECTIVE: To characterize change from baseline weight over time for pregabalin and placebo administration. METHODS: Asymptotic fraction of baseline weight was modeled with a nonmixture model and a mixture model as a function of baseline weight, exposure, time, covariate effects, and subject-specific random effects. Model fit was assessed using standard diagnostic plots. Predictive performance was assessed using both data similar to the original data, and open-label data. RESULTS: The nonmixture model indicated that a typical patient (baseline weight 82 kg) receiving placebo or 300 mg/day pregabalin approached an asymptotic fractional change from baseline weight of [mean (95% prediction interval for typical individual)] 0.7% (-5.5% to 7.4%) or 2.5% (-3.8% to 9.1%), respectively, with a half-life of 17 days. Substantial between-subject variability is observed, with some drug-treated subjects remaining weight neutral or losing weight, at all levels of exposure. Structural fixed effects parameters for the two submodels (mixture model) were in close agreement with each other and with those for the nonmixture model. The mixture model described two subpopulations differing in interindividual variability. No significant interindividual-varying covariates influencing the mixture probabilities were identified other than exposure. Both models had adequate fit; both models performed well during external validation. Predictive performance (nonmixture model) was adequate to ~900 days. CONCLUSIONS: The weight of a typical 82-kg patient receiving placebo or pregabalin (300 mg/day) approaches an asymptotic fractional change from baseline weight of 0.7%, or 2.5%, respectively, with a half-life of 17 days. Substantial between-subject variability remains unexplained.

Exposure-response analysis of pregabalin add-on treatment of patients with refractory partial seizures.

OBJECTIVE: Our objectives were to describe the exposure-response relationship of pregabalin add-on treatment for refractory partial seizures after multiple dosing in patients and to identify the factors that influence this relationship. METHODS: A mixed-effects model was used to characterize the relationship between monthly seizure frequency over a 3-month period and pregabalin daily dose (0, 50, 150, 300, and 600 mg) as add-on treatment in 3 double-blind, parallel-group studies in patients with refractory partial seizures (N = 1042). Seizure frequency was modeled as a Poisson process expressed as a function of baseline seizures, drug treatment, placebo effect, and subject-specific random effects. The model included a parameter that partitioned the population into subpopulations with respect to response. RESULTS: Seventy-five percent of patients showed an asymptotic decrease in seizure frequency with increasing doses of pregabalin, whereas 25% did not demonstrate a significant decrease in seizure frequency from baseline. In patients who demonstrated a dose-related decrease in seizure frequency from baseline, the maximal percentage of seizure reduction from baseline was 100% for women and 80% for men, with a 186-mg daily dose decreasing seizures on average to 50% of maximum. Age, race, and menopausal status did not significantly affect seizure frequency. CONCLUSION: Pregabalin add-on treatment demonstrates a dose-response relationship in 3 out of 4 patients with refractory partial seizures. A dose of 186 mg pregabalin daily is expected to decrease the seizure rate by 50% of maximum from baseline. Age, race, and menopausal status of women did not affect the dose-response relationship.