PK-DB an open database for pharmacokinetics information from clinical trials as well as pre-clinical research. The focus of PK-DB is to provide high-quality pharmacokinetics data enriched with the required meta-information for computational modeling and data integration.

This is a new, open, and transparent database of toxicokinetic data supporting EPA decision making. The database has already become the basis of research efforts within EPA to improve HTTK modeling using generic TK models and has facilitated the creation and validation of models for new exposure routes. Publishing the database supports open, transparent science and this database (the largest public database for this domain) will spur improvement and development of TK models by external experts in the field. Future efforts to improving the accessibility of this database (with a graphical user interface) and encouraging crowdsourcing to expand the size and scope of the database will lead to larger validation sets for our modeling efforts and likely lower uncertainties when estimating TK. This dataset is associated with the following publication: Sayre, R., J. Wambaugh, and C. Grulke. Database of pharmacokinetic time-series data and parameters for 144 environmental chemicals. Scientific Data. Springer Nature Group, New York, NY, 7: 122, (2020).

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Human dose prediction is increasingly recognized as an important parameter in Drug Discovery. Validation of a method using only in vitro and predicted parameters incorporated into a PK model was undertaken by predicting human dose and free Cmax for a number of marketed drugs and AZ Development compounds. Doses were compared to those most relevant to marketed drugs or to clinically administered doses of AZ compounds normalized either to predicted Cmin or Cmax values. Average (AFE) and absolute average (AAFE) fold-error analysis showed that best predictions were obtained using a QSAR model as the source of Vss, with Fabs set to 1 for acids and 0.5 for all other ion classes; for clearance prediction no binding correction to the well stirred model (WSM) was used for bases, while it was set to Fup/Fup0.5 for all other ion classes. Using this combination of methods, predicted doses for 45 to 68% of the Cmin- and Cmax-normalized and marketed drug data sets were within 3-fold of the observed values, while 82 to 92% of these data sets were within 10-fold. This method for early human dose prediction is able to rank, identify, and flag risks or optimization opportunities for future development compounds within 10 days of first synthesis.

Pakistan PK: Fixed Broadband Internet Subscribers data was reported at 1,829,673.000 Person in 2017. This records an increase from the previous number of 1,642,805.000 Person for 2016. Pakistan PK: Fixed Broadband Internet Subscribers data is updated yearly, averaging 1,166,301.000 Person from Dec 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 2,008,684.000 Person in 2014 and a record low of 14,600.000 Person in 2005. Pakistan PK: Fixed Broadband Internet Subscribers data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Telecommunication. Fixed broadband subscriptions refers to fixed subscriptions to high-speed access to the public Internet (a TCP/IP connection), at downstream speeds equal to, or greater than, 256 kbit/s. This includes cable modem, DSL, fiber-to-the-home/building, other fixed (wired)-broadband subscriptions, satellite broadband and terrestrial fixed wireless broadband. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It should include fixed WiMAX and any other fixed wireless technologies. It includes both residential subscriptions and subscriptions for organizations.; ; International Telecommunication Union, World Telecommunication/ICT Development Report and database.; Sum; Please cite the International Telecommunication Union for third-party use of these data.

Demographic characteristics of the 6–11 year olds included in the data analysis.

Increasing complexity of mAbs in development creates challenges in predicting human pharmacokinetic (PK) parameters from preclinical data. The aim of this analysis was to identify optimal allometric scaling exponents.Data were extracted from literature to create a central database (currently the largest available published database) of two-compartment model parameters for mAbs (n = 59) in cynomolgus monkey (CM) and human.Global allometric exponents were calculated and drug-dependent factors were investigated as potential variables in determining the optimal scaling factor.The global exponents for scaling CM mAb PK data were 0.74 (CL), 0.80 (CL with Fc-modified mAbs excluded), 0.44 (CL with Fc-modified mAbs only), 0.71 (Q), 1.12 (V1), and 0.99 (V2). These values are in line with previously published literature values. Increasing complexity of mAbs in development creates challenges in predicting human pharmacokinetic (PK) parameters from preclinical data. The aim of this analysis was to identify optimal allometric scaling exponents. Data were extracted from literature to create a central database (currently the largest available published database) of two-compartment model parameters for mAbs (n = 59) in cynomolgus monkey (CM) and human. Global allometric exponents were calculated and drug-dependent factors were investigated as potential variables in determining the optimal scaling factor. The global exponents for scaling CM mAb PK data were 0.74 (CL), 0.80 (CL with Fc-modified mAbs excluded), 0.44 (CL with Fc-modified mAbs only), 0.71 (Q), 1.12 (V1), and 0.99 (V2). These values are in line with previously published literature values.

Pakistan PK: High-Technology Exports: % of Manufactured Exports data was reported at 1.908 % in 2016. This records an increase from the previous number of 1.557 % for 2015. Pakistan PK: High-Technology Exports: % of Manufactured Exports data is updated yearly, averaging 1.187 % from Dec 1990 (Median) to 2016, with 26 observations. The data reached an all-time high of 1.908 % in 2016 and a record low of 0.025 % in 1991. Pakistan PK: High-Technology Exports: % of Manufactured Exports data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Technology. High-technology exports are products with high R&D intensity, such as in aerospace, computers, pharmaceuticals, scientific instruments, and electrical machinery.; ; United Nations, Comtrade database through the WITS platform.; Weighted average;

Pakistan PK: Stocks Traded: Total Value data was reported at 27.536 USD bn in 2016. This records an increase from the previous number of 27.108 USD bn for 2015. Pakistan PK: Stocks Traded: Total Value data is updated yearly, averaging 20.824 USD bn from Dec 1996 (Median) to 2016, with 21 observations. The data reached an all-time high of 140.293 USD bn in 2004 and a record low of 539.700 USD mn in 2014. Pakistan PK: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

3473 Global import shipment records of Pk Plastic with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Our Pakistan zip code Database offers comprehensive postal code data for spatial analysis, including postal and administrative areas. This dataset contains accurate and up-to-date information on all administrative divisions, cities, and zip codes, making it an invaluable resource for various applications such as address capture and validation, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including CSV, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Product features include fully and accurately geocoded data, multi-language support with address names in local and foreign languages, comprehensive city definitions, and the option to combine map data with UNLOCODE and IATA codes, time zones, and daylight saving times. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

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Pakistan PK: Tuberculosis Case Detection Rate: All Forms data was reported at 69.000 % in 2016. This records an increase from the previous number of 63.000 % for 2015. Pakistan PK: Tuberculosis Case Detection Rate: All Forms data is updated yearly, averaging 54.000 % from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 69.000 % in 2016 and a record low of 2.900 % in 2000. Pakistan PK: Tuberculosis Case Detection Rate: All Forms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Health Statistics. Tuberculosis case detection rate (all forms) is the number of new and relapse tuberculosis cases notified to WHO in a given year, divided by WHO's estimate of the number of incident tuberculosis cases for the same year, expressed as a percentage. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.; ; World Health Organization, Global Tuberculosis Report.; Weighted average;

Pakistan PK: Human Capital Index (HCI): Upper Bound: Scale 0-1 data was reported at 0.404 NA in 2017. Pakistan PK: Human Capital Index (HCI): Upper Bound: Scale 0-1 data is updated yearly, averaging 0.404 NA from Dec 2017 (Median) to 2017, with 1 observations. Pakistan PK: Human Capital Index (HCI): Upper Bound: Scale 0-1 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Human Capital Index. The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.; ; World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498; ;

Schedule of simulated scenarios.

Estimates of the parameters from the base model and final selected model.

Design optimisation for a study in 2–5 year olds.

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