https://orcid.org/0000-0001-8699-1412
Healthcare professionals face increasing challenges in managing older patients in daily practice, particularly those suffering from multiple comorbid states [Citation1]. Clinical guidelines and recommendations driving routine clinical decisions are primarily generated using evidence from randomized controlled trials that investigate the effects of specific drugs for the treatment of individual diseases [Citation2]. However, the clinical complexity of older multimorbid patients typically prevents them from meeting the stringent inclusion and exclusion criteria of randomized controlled trials [Citation3,Citation4]. As a consequence, there is a concerning lack of robust, real-world evidence for treating this highly heterogenous population safely and effectively also given the ever-increasing number of marketed drugs [Citation5]. Additionally, traditional disease management typically follows a single disease approach to care that is not adapted to the needs of persons with multimorbidity where the potential for inappropriate polypharmacy, medication interactions, and unwanted effects is greatly increased [Citation6].
These vexing issues notwithstanding, the last decade has witnessed significant advances particularly in the discovery of novel biomarkers and druggable targets for several age-related disease states [Citation7], the identification of factors, e.g., frailty and sarcopenia, modulating the complex interplay between patient, drugs, and diseases [Citation8], and the development of strategies for targeting inappropriate polypharmacy [Citation9]. These critical developments, in association with the recent and rapid rise in the use or artificial intelligence and machine learning techniques for the identification of new safety signals and therapeutic applications using big data [Citation10], offer unprecedented opportunities for research in geriatric pharmacology that is aimed to improve the therapeutic management of older people.
Therefore, this appears to be an exciting time to develop a new journal that is entirely focused on various aspects of pharmacology that are directly relevant to the needs of the older patient population. Geriatric Pharmacology, a new fully open access journal, has successfully managed to attract highly reputable and experienced editorial board members, including worldwide experts in various aspects of basic, translational, and clinical pharmacology applicable to the ageing process and the therapeutic management of older patients. The recruitment, as Associate Editors, of Dr Roy Soiza, a senior geriatrician and international expert in clinical pharmacology in old age, and Professor Richard Woodman, a widely recognized biostatistician with interests in pharmacoepidemiology and the use of artificial intelligence and machine learning for medicine and healthcare, will further raise the scientific profile and the reputation of the new journal.
By considering a wide range of submissions in basic science, clinical research, qualitative studies, and new directions in artificial intelligence and machine learning, we look forward to developing Geriatric Pharmacology and running article collections on key new topics in these fields. We are confident that the new journal is uniquely placed to capture the exciting momentum in ageing-associated pharmacological research by disseminating robust science that will ultimately enhance the use of medications in older people.
References
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- Turk A, Wong G, Mahtani KR, et al. Optimising a person-centred approach to stopping medicines in older people with multimorbidity and polypharmacy using the DExTruS framework: a realist review. BMC Med. 2022 Aug 31;20(1):297.
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- Sayer AA, Cruz-Jentoft A. Sarcopenia definition, diagnosis and treatment: consensus is growing. Age Ageing. 2022 Oct 6;51(10).
- Woodman RJ, Mangoni AA. A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future. Aging Clin Exp Res. 2023 Sep 8.