Evidence map›Paper›PMID 42713263›Full record

ReviewFrontiers in pharmacology2026

Digital health in clinical pharmacy practice: transforming precision medicine and pharmacometrics in Africa.

Sumaiah J Alarfaj, Engy Wahsh, Khaled Saad, Eman S Sawan

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sumaiah J AlarfajDepartment of Pharmacy Practice, College of Pharmacy, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Engy WahshClinical Pharmacy Department, Faculty of Pharmacy, October 6 University, Giza, Egypt.
Khaled SaadDepartment of Pediatrics, Faculty of Medicine, Assiut University, Asyut, Egypt.
Eman S SawanDepartment of Clinical Pharmacy, Faculty of Pharmacy, Badr University in Cairo (BUC), Badr, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

African nations still struggle with several healthcare challenges such as high prevalence of communicable and non-communicable diseases, underdeveloped healthcare systems, lack of healthcare personnel, and uneven distribution of quality healthcare services. Resource constraints and a fragmented healthcare system make the aforementioned challenges even more difficult to solve. However, digital health technology and artificial intelligence (AI) can be viewed as revolutionary instruments that may help to overcome the mentioned challenges and enhance healthcare practices in Africa. The present article provides a review of how digital health technologies and AI influence clinical pharmacy practice and contribute to precision medicine and pharmacometrics in African nations. To do that, a literature search has been performed using the PubMed, Scopus, and Web of Science electronic databases for relevant articles about digital health, AI, clinical pharmacy, precision medicine, pharmacometrics, and healthcare delivery in Africa. Healthcare technologies, such as telemedicine, mobile health apps, electronic health records, and clinical decision support systems powered by AI, are becoming more pervasive and widening the scope of work for clinical pharmacists through their contribution to medication optimization, therapeutic monitoring, and evidence-based clinical decision-making. Their application within precision medicine allows creating an individual treatment strategy considering the genetic and clinical features of the patients. At the same time, pharmacometric approaches, especially pharmacokinetics and pharmacodynamics modeling and model-informed precision dosing, help to optimize drug prescription and therapy outcomes for different African populations. The present article provides a review of how integrating digital health technologies and AI into clinical pharmacy practice could be a promising approach for enhancing precision medicine in Africa. The review also explores their implementation challenges and future opportunities for reasonable healthcare delivery.

Indexed as

Africaartificial intelligenceclinical decision support systemsclinical pharmacydigital healthelectronic health recordsmodel-informed precision dosingpharmacogenomics

Identifiers

PMID42713263
PMCPMC13551482

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.