The following dataset is the World Drug Report 2021 produced by the United Nations Office on Drugs and Crime. https://www.unodc.org/unodc/en/data-and-analysis/wdr2021_annex.html

The Executive Summary: https://www.unodc.org/res/wdr2021/field/WDR21_Booklet_1.pdf

Special points of interest from the report: - Cannabis has come to be seen as less risky by adolescents from 1995 to 2019, but the herb potency has increased 4x in that time period. - Web-based sales have increased dramatically. - Number of drug users in Africa is projected to rise by 40 per cent by 2030, based on expected population growth in the 15-64 demographic. - Drug markets quickly recovered after the onset of the pandemic, but some trafficking dynamics have been accelerated during Covid-19 - Non-medical use of cannabis and sedatives has increased globally during the pandemic

On Opioids specifically: - The two pharmaceutical opioids most commonly used to treat people with opioid use disorders, methadone and buprenorphine, have become increasingly accessible over the past two decades. The amount available for medical use has increased sixfold since 1999, from 557 million daily doses in that year to 3,317 million by 2019. - The amounts of fentanyl and its analogues seized globally have risen rapidly in recent years, and by more than 60 per cent in 2019 compared with a year earlier. Overall, these amounts have risen more than twenty-fold since 2015. The largest quantities were seized in North America. - Elsewhere in the world, other pharmaceutical opioids (codeine and tramadol) predominate. Over the period 2015–2019, the largest quantities of tramadol seized were reported in West and Central Africa; they accounted for 86 per cent of the global total. Codeine was intercepted in large quantities in Asia, often in the form of diverted cough syrups. - Almost 50,000 people died from overdose deaths attributed to opioids in the United States in 2019, more than double the 2010 figure. By comparison, in the European Union, the figure for all drug-related overdoses (mostly relating to opioid use) stood at 8,300 in 2018, despite the larger population. - However, the opioid crisis in North America is evolving. The number of deaths attributed to heroin and the non-medical use of pharmaceutical opioids such as oxycodone or hydrocodone has been declining over the past five years. - The crisis is now driven mainly by overdose deaths attributed to synthetic opioids such as fentanyl and its analogues. Among the reasons for the large number of overdose deaths attributed to fentanyls is that the lethal doses of them are often small when compared with other opioids. Fentanyl is up to 100 times more potent than morphine. - The impact of fentanyl is illustrated even further by the fact that more than half of the deaths attributed to heroin also involve fentanyls. Synthetic opioids also contribute significantly to the increased number of overdose deaths attributed to cocaine and other psychostimulants, such as methamphetamine.

Abstract (en): This data collection is part of the Monitoring the Future series that explores changes in important values, behaviors, and lifestyle orientations of contemporary American youth in eighth, tenth, and twelfth grades. The collection provides two datasets for each year since 1976 that are accessible only through the ICPSR Virtual Data Enclave VDE) and include original variables, including the unaltered weight variable, that in the public-use data were altered or omitted: one dataset without State, County, and Zip Code and one dataset including State, County, and Zip Code. Use of the geographic identifiers such as state, county, or zip code is limited and researchers interested in these variables are encouraged to read FAQs: About MTF Restricted-Use Geographic and Other Variables. Also included as part of each annual collection is a zip archive of the Monitoring the Future public-use data and documentation for each respective year. The basic research design used by the Monitoring the Future study involves annual data collections from eighth, tenth, and twelfth graders throughout the coterminous United States during the spring of each year. The 8th/10th grade surveys used four different questionnaire forms (and only two forms from 1991-1996) rather than the six used with seniors. Identical forms are used for both eighth and tenth grades, and for the most part, questionnaire content is drawn from the twelfth-grade questionnaires. Thus, key demographic variables and measures of drug use and related attitudes and beliefs are generally identical for all three grades. However, many fewer questions about lifestyles and values are included in the 8th/10th grade forms. Drugs covered by this survey include tobacco, smokeless tobacco, alcohol, marijuana, hashish, prescription medications, over-the-counter medications, inhalants, steroids, LSD, hallucinogens, amphetamines (stimulants), Ritalin (methylphenidate), Quaaludes (methaqualone), barbiturates (tranquilizers), cocaine, crack cocaine, ecstasy, methamphetamine, heroin, and GHB (gamma hydroxy butyrate). Other topics include attitudes toward religion, changing roles for women, educational aspirations, self-esteem, exposure to drug education, and violence and crime (both in and out of school). ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Checked for undocumented or out-of-range codes.. Response Rates: See Appendix B in the codebook for information about response rates. Datasets:DS0: Study-Level FilesDS1: Restricted-Use Variables Without State, County, and Zip Code (VDE Only)DS2: Restricted-Use Variables Including State, County, and Zip Code (VDE Only)DS3: Copy of Public-Use Files Eighth, tenth, and twelfth grade students in the contiguous United States. Smallest Geographic Unit: Zip code A multistage area probability sample design was used involving three selection stages: (1) geographic areas or primary sampling units (PSUs), (2) schools (or linked groups of schools) within PSUs, and (3) students within sampled schools. For more information, see the Sampling Information in the codebook introduction and Sample Size and Student Response Rates in Appendix B. 2019-08-19 Additional height and weight variables were added to Dataset 1 and Dataset 2. The county variable was also added to Dataset 2. Funding institution(s): United States Department of Health and Human Services. National Institutes of Health. National Institute on Drug Abuse (DA001411). on-site questionnaire

United States Imports of Pharmaceutical products was US$212.67 Billion during 2024, according to the United Nations COMTRADE database on international trade. United States Imports of Pharmaceutical products - data, historical chart and statistics - was last updated on December of 2025.

According to Cognitive Market Research, the global Artificial Intelligence / AI in Drug Discovery market size is USD 0.6 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 40.00% from 2024 to 2031.

North America is set to grow dominate the market with a share of XX% and a CAGR of XX% from 2025-2033.
South America constitutes about XX% of market share of and is expected to grow at a CAGR of XX% from 2025-2033.
Europe constitutes a share of XX% of Artificial Intelligence Ai In Drug Discovery Market and is expected to grow at a CAGR of XX% from 2025-2033.
Asia-Pacific is growing at the fastest CAGR in the Artificial Intelligence Ai In Drug Discovery Market with a share of XX% and is expected CAGR of XX% from 2025-2033.
Africa and the Middle-East is expected to grow at a CAGR of XX% and has a market share of XX% in the Artificial Intelligence Ai In Drug Discovery Market.

Market Dynamics of Artificial Intelligence / AI in Drug Discovery Market

Key Drivers for Artificial Intelligence / AI in Drug Discovery Market

Growing Need to Control Drug Discovery and Development Costs to Increase the Demand Globally.

One key driver in the Artificial Intelligence / AI in Drug Discovery market is the growing need to control drug discovery and development costs. This trend underscores a crucial shift in the pharmaceutical landscape, where cost-effectiveness becomes paramount. As companies seek more efficient methods and technologies, there's a growing emphasis on optimizing processes to drive innovation and meet the needs of a rapidly evolving market. Precision Medicine Enhances Treatment Efficacy

Key Restraints for Artificial Intelligence / AI in Drug Discovery Market

Availability of suitable data for AI algorithms restraining the market The limited availability of suitable data poses a significant restraint in the application of artificial intelligence (AI) in drug discovery. AI-driven models, particularly deep learning algorithms, require extensive, high-quality datasets to train effectively. However, in many instances, accessible data may be limited, of suboptimal quality, or inconsistent, thereby compromising the accuracy and reliability of the results. This challenge is compounded by issues such as data fragmentation, where valuable biomedical data is siloed within various organizations, hindering effective collaboration and impeding the drug discovery process. Moreover, the complexity of biological systems introduces additional hurdles, as existing AI models may not fully capture the dynamic interactions within cellular environments, leading to oversimplifications and errors. To address these challenges, strategies like data augmentation, federated learning, and the adoption of FAIR (Findable, Accessible, Interoperable, and Reusable) data principles are being explored to enhance data accessibility and quality, thereby improving the efficacy of AI in drug discovery. References: https://pmc.ncbi.nlm.nih.gov/articles/PMC10302890/#B40-pharmaceuticals-16-00891 https://www.sciencedirect.com/science/article/abs/pii/S0010482524008199 Market Overview

The Artificial intelligence (AI) in drug discovery employs sophisticated computational algorithms and machine learning models to analyze biological data, anticipate potential drug candidates, and hasten the drug development process. AI facilitates uncovering novel drug targets, refining molecular structures, and scrutinizing extensive datasets, thereby empowering researchers to uncover innovative and enhanced therapeutic options. One of the key drivers propelling the growth of the Artificial Intelligence / AI in Drug Discovery market is the widespread adoption of digital health solutions. These technologies offer remote patient monitoring, telemedicine services, and personalized healthcare delivery, improving patient outcomes and reducing costs. Integration of artificial intelligence (AI) and machine learning enhances data analytics, enabling healthcare providers to make informed decisions.

Temporal trends in dyslipidemia prevalence and medication prescriptions in the study cohort.

Model adjusted for age, gender, education, employment status, disease complexity, mortality risk, depression, substance abuse (heroin and/or cocaine use), and insurance Status, bold indicates P