Structured Data Entry for Reliable Acquisition of Pharmacokinetic Data

1996 ◽  
Vol 35 (03) ◽  
pp. 261-264 ◽  
Author(s):  
T. Schromm ◽  
T. Frankewitsch ◽  
M. Giehl ◽  
F. Keller ◽  
D. Zellner
Keyword(s):  
Text Processing ◽  
Data Entry ◽  
Processing System ◽  
Database System ◽  
Structured Data ◽  
Pharmacokinetic Parameters ◽  
Pharmacokinetic Data ◽  
Probability Of Error ◽  
Error Frequency ◽  
Estimated Error

Abstract:A pharmacokinetic database was constructed that is as free of errors as possible. Pharmacokinetic parameters were derived from the literature using a text-processing system and a database system. A random data sample from each system was compared with the original literature. The estimated error frequencies using statistical methods differed significantly between the two systems. The estimated error frequency in the text-processing system was 7.2%, that in the database system 2.7%. Compared with the original values in the literature, the estimated probability of error for identical pharmacokinetic parameters recorded in both systems is 2.4% and is not significantly different from the error frequency in the database. Parallel data entry with a text-processing system and a database system is, therefore, not significantly better than structured data entry for reducing the error frequency.

A Model for Structured Data Entry Based on Explicit Descriptional Knowledge

1994 ◽  
Vol 33 (05) ◽  
pp. 454-463 ◽  
Author(s):  
A. M. van Ginneken ◽  
J. van der Lei ◽  
J. H. van Bemmel ◽  
P. W. Moorman
Keyword(s):  
Domain Knowledge ◽  
Data Entry ◽  
Knowledge Bases ◽  
Structured Data ◽  
Research Quality ◽  
Free Text ◽  
Specific Knowledge ◽  
User Input ◽  
The One ◽  
Research Quality Assessment

Abstract:Clinical narratives in patient records are usually recorded in free text, limiting the use of this information for research, quality assessment, and decision support. This study focuses on the capture of clinical narratives in a structured format by supporting physicians with structured data entry (SDE). We analyzed and made explicit which requirements SDE should meet to be acceptable for the physician on the one hand, and generate unambiguous patient data on the other. Starting from these requirements, we found that in order to support SDE, the knowledge on which it is based needs to be made explicit: we refer to this knowledge as descriptional knowledge. We articulate the nature of this knowledge, and propose a model in which it can be formally represented. The model allows the construction of specific knowledge bases, each representing the knowledge needed to support SDE within a circumscribed domain. Data entry is made possible through a general entry program, of which the behavior is determined by a combination of user input and the content of the applicable domain knowledge base. We clarify how descriptional knowledge is represented, modeled, and used for data entry to achieve SDE, which meets the proposed requirements.

scholarly journals Pharmacokinetics and Molecular Modeling Indicate nAChRα4-Derived Peptide HAEE Goes through the Blood–Brain Barrier

Biomolecules ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 909
Author(s):  
Yurii A. Zolotarev ◽  
Vladimir A. Mitkevich ◽  
Stanislav I. Shram ◽  
Alexei A. Adzhubei ◽  
Anna P. Tolstova ◽  
...  
Keyword(s):  
Molecular Modeling ◽  
Mouse Model ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Laboratory Animals ◽  
Pharmacokinetic Parameters ◽  
Pharmacokinetic Data ◽  
Bolus Administration ◽  
Blood Brain ◽  
The Brain

One of the treatment strategies for Alzheimer’s disease (AD) is based on the use of pharmacological agents capable of binding to beta-amyloid (Aβ) and blocking its aggregation in the brain. Previously, we found that intravenous administration of the synthetic tetrapeptide Acetyl-His-Ala-Glu-Glu-Amide (HAEE), which is an analogue of the 35–38 region of the α4 subunit of α4β2 nicotinic acetylcholine receptor and specifically binds to the 11–14 site of Aβ, reduced the development of cerebral amyloidogenesis in a mouse model of AD. In the current study on three types of laboratory animals, we determined the biodistribution and tissue localization patterns of HAEE peptide after single intravenous bolus administration. The pharmacokinetic parameters of HAEE were established using uniformly tritium-labeled HAEE. Pharmacokinetic data provided evidence that HAEE goes through the blood–brain barrier. Based on molecular modeling, a role of LRP1 in receptor-mediated transcytosis of HAEE was proposed. Altogether, the results obtained indicate that the anti-amyloid effect of HAEE, previously found in a mouse model of AD, most likely occurs due to its interaction with Aβ species directly in the brain.

American National Standard for Human Factors Engineering of Visual Display Terminal Workstations: A Report to the Society

1985 ◽  
Vol 29 (10) ◽  
pp. 987-987 ◽  
Author(s):  
Gene Lynch
Keyword(s):  
Human Factors ◽  
Text Processing ◽  
Data Entry ◽  
Visual Display ◽  
Measurement Methods ◽  
National Standards ◽  
National Standard ◽  
Human Factors Engineering ◽  
Visual Display Terminal ◽  
The Individual

The American National Standard for Human Factors Engineering of Visual Display Terminal Workstations, the first standard sponsored by the Human Factors Society, is in the final stages of acceptance as an American National Standard. This standard addresses the physical and perceptual aspects of the visual display terminal workstation as used in text processing, data entry, and data inquiry. Standards take on many different forms and fill a variety of needs. Basically a standard provides a reference. Some standards are written so that two systems may be designed to complement each other or fit together. Lightbulbs and fixtures designed to the same standard will work together. In the case of human factors standards one half of the system is already designed, the human. The variety of the design of this part of the system requires that human factors standards identify the parameters to be considered and the corresponding measurement methods needed to insure that the equipment is designed to fit the individual human. A good solution needs to be based on the particular set of circumstances at hand. The voluntary standards method, known as the American National Standards, provides a vehicle for specifying the appropriate parameters and measurement methods while incorporating the necessary flexibility required to insure good designs for individuals. The purpose of this panel session is to provide the society with an interactive session with representatives of the standards drafting committee. A brief history of the committee and its activities will be presented. The panelists will then describe the approach taken in each of the major sections, the mandatory requirements, and the elements the panelists consider to be of particular interest

Relationship between Clinical and Biologic Variables and Chloramphenicol Pharmacokinetic Parameters in Pediatric Patients with Sepsis

2000 ◽  
Vol 34 (3) ◽  
pp. 393-397 ◽  
Author(s):  
Gustavo Lugo Goytia ◽  
Ismael Lares-Asseff ◽  
María Gabriela Pérez Guillé ◽  
Adrián Guillé Pérez ◽  
Cynthia Larios Mejía
Keyword(s):  
Population Model ◽  
Pediatric Patients ◽  
Care Center ◽  
Tertiary Care ◽  
Pharmacokinetic Parameters ◽  
Pharmacokinetic Data ◽  
Study Group ◽  
Validation Group ◽  
Wbc Count ◽  
Biologic Factors

OBJECTIVE: To evaluate the influence of several clinical and biologic factors on the disposition kinetics of oral chloramphenicol in pediatric patients and to determine the usefulness of this information to predict chloramphenicol serum concentrations. STUDY DESIGN: The clinical, biologic, and pharmacokinetic data of 30 consecutive pediatric patients diagnosed with sepsis and admitted to a tertiary care center were analyzed retrospectively. The patients were randomly assigned to a study group and a validation group. The model was developed by a three-step approach involving Bayesian estimation of pharmacokinetic parameters, selection of covariates by principal component analysis, and final selection by stepwise multiple linear regression. The model was tested in the study group and compared with a general population model using a prediction error analysis. RESULTS: Regression analysis revealed that weight, albumin, and white blood cell (WBC) count were the most important determinants for chloramphenicol distribution volume, whereas age, WBC count, and serum creatinine were the most important determinants for chloramphenicol clearance. The performance of the constructed population model improved significantly in terms of both bias and precision compared with the general model when tested in the validation group. CONCLUSIONS: Clinical and biologic factors may significantly influence chloramphenicol's disposition in pediatric patients with sepsis and therefore should be considered in programming dosage regimens.

scholarly journals Predicting absorption and pharmacokinetic profile of carbamazepine from controlled-release tablet formulation in humans using rabbit model

2011 ◽  
Vol 65 (1-2) ◽  
pp. 71-81
Author(s):  
Irena Homsek ◽  
Dragica Popadic ◽  
Slobodanka Simic ◽  
Slavica Ristic ◽  
Katarina Vucicevic ◽  
...  
Keyword(s):  
Controlled Release ◽  
Rabbit Model ◽  
Tablet Formulation ◽  
Human Model ◽  
In Vitro Dissolution ◽  
Pharmacokinetic Parameters ◽  
Pharmacokinetic Data ◽  
Drug Concentrations

Controlled-release (CR) pharmaceutical formulations offer several advantages over the conventional, immediate release dosage forms of the same drug, including reduced dosing frequency, decreased incidence and/or intensity of adverse effects, greater selectivity of pharmacological activity, reduced drug plasma fluctuation, and better compliance. After a drug product has been registered, and is already on market, minor changes in formulation might be needed. At the same time, the product has to remain effective and safe for patients that could be confirmed via plasma drug concentrations and pharmacokinetic characteristics. It is challenging to predict human absorption and pharmacokinetic characteristics of a drug based on the in vitro dissolution test and the animal pharmacokinetic data. Therefore, the objective of this study was to establish correlation of the pharmacokinetic parameters of carbamazepine (CBZ) CR tablet formulation between the rabbit and the human model, and to establish in vitro in vivo correlation (IVIVC) based on the predicted fractions of absorbed CBZ. Although differences in mean plasma concentration profiles were notified, the data concerning the predicted fraction of drug absorbed were almost superimposable. Accordingly, it can be concluded that rabbits may be representative as an in vivo model for predicting the pharmacokinetics of the CR formulation of CBZ in humans.

scholarly journals Proof-of-Concept Study of Drug Brain Permeability Between in Vivo Human Brain and an in Vitro iPSCs-Human Blood-Brain Barrier Model

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Gwenaëlle Le Roux ◽  
Rafika Jarray ◽  
Anne-Cécile Guyot ◽  
Serena Pavoni ◽  
Narciso Costa ◽  
...  
Keyword(s):  
Human Brain ◽  
Blood Brain Barrier ◽  
Brain Barrier ◽  
Pharmacokinetic Parameters ◽  
Pharmacokinetic Data ◽  
Apparent Permeability ◽  
Clinical Drug Development ◽  
Blood Brain

Abstract The development of effective central nervous system (CNS) drugs has been hampered by the lack of robust strategies to mimic the blood-brain barrier (BBB) and cerebrovascular impairments in vitro. Recent technological advancements in BBB modeling using induced pluripotent stem cells (iPSCs) allowed to overcome some of these obstacles, nonetheless the pertinence for their use in drug permeation study remains to be established. This mandatory information requires a cross comparison of in vitro and in vivo pharmacokinetic data in the same species to avoid failure in late clinical drug development. Here, we measured the BBB permeabilities of 8 clinical positron emission tomography (PET) radioligands with known pharmacokinetic parameters in human brain in vivo with a newly developed in vitro iPSC-based human BBB (iPSC-hBBB) model. Our findings showed a good correlation between in vitro and in vivo drug brain permeability (R2 = 0.83; P = 0.008) which contrasted with the limited correlation between in vitro apparent permeability for a set of 18 CNS/non-CNS compounds using the in vitro iPSCs-hBBB model and drug physicochemical properties. Our data suggest that the iPSC-hBBB model can be integrated in a flow scheme of CNS drug screening and potentially used to study species differences in BBB permeation.

scholarly journals Automating the Capture of Structured Pathology Data for Prostate Cancer Clinical Care and Research

2019 ◽  
pp. 1-8 ◽  
Author(s):  
Anobel Y. Odisho ◽  
Mark Bridge ◽  
Mitchell Webb ◽  
Niloufar Ameli ◽  
Renu S. Eapen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Gold Standard ◽  
Clinical Care ◽  
Data Entry ◽  
Structured Data ◽  
Lymph Node Status ◽  
Free Text ◽  
Routine Clinical Care ◽  
Pathology Reports ◽  
Pathology Data

Purpose Cancer pathology findings are critical for many aspects of care but are often locked away as unstructured free text. Our objective was to develop a natural language processing (NLP) system to extract prostate pathology details from postoperative pathology reports and a parallel structured data entry process for use by urologists during routine documentation care and compare accuracy when compared with manual abstraction and concordance between NLP and clinician-entered approaches. Materials and Methods From February 2016, clinicians used note templates with custom structured data elements (SDEs) during routine clinical care for men with prostate cancer. We also developed an NLP algorithm to parse radical prostatectomy pathology reports and extract structured data. We compared accuracy of clinician-entered SDEs and NLP-parsed data to manual abstraction as a gold standard and compared concordance (Cohen’s κ) between approaches assuming no gold standard. Results There were 523 patients with NLP-extracted data, 319 with SDE data, and 555 with manually abstracted data. For Gleason scores, NLP and clinician SDE accuracy was 95.6% and 95.8%, respectively, compared with manual abstraction, with concordance of 0.93 (95% CI, 0.89 to 0.98). For margin status, extracapsular extension, and seminal vesicle invasion, stage, and lymph node status, NLP accuracy was 94.8% to 100%, SDE accuracy was 87.7% to 100%, and concordance between NLP and SDE ranged from 0.92 to 1.0. Conclusion We show that a real-world deployment of an NLP algorithm to extract pathology data and structured data entry by clinicians during routine clinical care in a busy clinical practice can generate accurate data when compared with manual abstraction for some, but not all, components of a prostate pathology report.

Are Structured Data Structured Identically?

2005 ◽  
Vol 44 (05) ◽  
pp. 631-638 ◽  
Author(s):  
J. Roukema ◽  
A. M. van Ginneken ◽  
M. de Wilde ◽  
J. van der Lei ◽  
R. K. Los
Keyword(s):  
Clinical Practice ◽  
Data Use ◽  
Data Entry ◽  
Patient Data ◽  
Structured Data ◽  
Free Text ◽  
Patient Records ◽  
Paper Record ◽  
Recorded Data ◽  
Insight Into

Summary Objective: OpenSDE is an application that supports structured recording of narrative patient data to enable use of the data in both clinical practice and clinical research. Reliability and accuracy of collected data are essential for subsequent data use. In this study we analyze the uniformity of data entered with OpenSDE. Our objective is to obtain insight into the consensus and differences of recorded data. Methods: Three pediatricians transcribed 20 paper patient records using OpenSDE. The transcribed records were compared and all recorded findings were classified into one of six categories of difference. Results: Of all findings 22% were recorded identically; 17% of the findings were recorded differently (predominantly as free text); 61% was omitted, inferred, or in conflict with the paper record. Conclusion: The results of this study show that recording patient data using structured data entry does not necessarily lead to uniformly structured data.

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