Biofarma - Multidisciplinary Scientific Journal of Biology, Pharmacy and Health

THE INTERSECTION OF PHARMACY, TECHNOLOGY AND PHARMACY PRACTICE

2024-10-28T18:07:16+00:00

This study examines the transformation of the pharmacist's role, highlighting the increasing incorporation of technology in pharmacies and its effect on the quality of patient care. The research indicates that tools such as telemedicine and monitoring applications have improved accessibility and treatment adherence, resulting in greater patient satisfaction with pharmaceutical services. Additionally, the use of artificial intelligence has contributed to reducing potentially dangerous drug interactions. However, digitalization in the pharmaceutical sector presents ethical challenges and data privacy concerns that need to be carefully addressed.

PHARMACOLOGICAL INNOVATIONS AND NEUROSCIENCES IN HEALTHCARE

2024-10-28T18:28:26+00:00

This article discusses emerging innovations in drug treatments, exploring their intersection with neuroscientific discoveries. We analyze the impact of these innovations on nursing practices and public health policies, emphasizing the need to adapt professional training and health systems to maximize benefits for the population. We discuss contemporary challenges such as drug resistance, the growing need for holistic approaches to patient care, and the use of technology for monitoring and interventions.

INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE PHARMACEUTICAL PROCESS: CHALLENGES AND OPPORTUNITIES

2024-10-28T15:03:40+00:00

The integration of Artificial Intelligence (AI) into the pharmaceutical process represents a transformative shift in how drugs are designed, tested, and brought to market. AI technologies, such as machine learning and natural language processing, enable pharmaceutical companies to analyze vast datasets, uncover patterns, and make informed decisions more efficiently than traditional methods. One of the key challenges in this integration is the need for high-quality data; the success of AI algorithms heavily relies on the accuracy and comprehensiveness of the information fed into them. Additionally, regulatory compliance and data privacy are significant concerns that require careful navigation. Despite these challenges, the opportunities presented by AI in the pharmaceutical sector are substantial. AI can expedite drug discovery, optimize clinical trial designs, and personalize treatment plans, ultimately leading to improved patient outcomes. Moreover, AI-driven predictive analytics can help in anticipating market trends and consumer needs, allowing companies to stay competitive. As the industry evolves, collaboration among stakeholders—including tech firms, regulatory agencies, and healthcare providers—will be critical to harness the full potential of AI. By embracing this technological advancement, the pharmaceutical industry can enhance efficiency, reduce costs, and bring innovative therapies to patients more rapidly.

FUTURE DEVELOPMENTS IN BRAIN-MACHINE INTERFACE RESEARCH

2024-10-30T21:15:16+00:00

This article explores future developments in brain-machine interface (BMI) research, highlighting its advances, challenges, and prospects. BMI represents a dynamic intersection between neuroscience, engineering, and medicine, rapidly advancing toward restoring motor functions in individuals with severe disabilities. Future research should address ethical issues, the accuracy of neural signals, and the development of more accessible and noninvasive devices. Although BMIs show significant potential, many technical and social hurdles remain to be overcome.

PHARMACOLOGICAL AND NON-PHARMACOLOGICAL INTERVENTIONS IN MATERNAL AND NEUROLOGICAL HEALTH

2024-10-31T15:20:25+00:00

This issue of Biopharma Perspectives will offer an in-depth analysis of emerging research with summaries of relevant studies, highlighting their clinical and practical implications for healthcare professionals. This new initiative aims to provide readers with a comprehensive understanding of the latest scientific innovations and their potential impacts on clinical practice, always aiming to improve the quality of patient care.

1. What are the benefits and risks of different non-pharmacological treatments for managing constipation and fecal incontinence in people with central neurological disease? This summary addresses health treatment options, linked to the impact of biology and pharmacology on chronic conditions.
2. What are the benefits and risks of medications for retained placenta after vaginal delivery? Research on medications in maternal health settings is crucial to better understand postpartum treatments and their implications.
3. What are the benefits and risks of different treatments that can delay or slow the progression of progressive multiple sclerosis? This summary addresses health treatment options, linked to the impact of biology and pharmacology on chronic conditions.

THE INFLUENCE OF VIRTUAL REALITY ON THE COGNITIVE REHABILITATION OF PATIENTS WITH CRANIOBRAIN INJURY: A CASE STUDY OF ‘LUCAS’

2024-10-30T20:48:40+00:00

This study presents a case of cognitive rehabilitation of Lucas, a 34-year-old patient who suffered a traumatic brain injury (TBI) in a car accident. Using virtual reality (VR) technology integrated with traditional neuropsychology techniques, Lucas participated in 12 sessions over three months. The intervention focused on improving executive functions, attention and memory. Research developed by the Biofarma Study Center corroborates the effectiveness of virtual reality in maximizing neuroplasticity and cognitive rehabilitation in patients with TBI.

THE TRANSFORMATIVE ROLE OF ARTIFICIAL INTELLIGENCE IN PERSONALIZED MEDICINE: A NEW FRONTIER AT THE BIOFARMA STUDY CENTER

2024-10-28T19:27:17+00:00

Personalized medicine, by recognizing individual variations that impact health, is being profoundly transformed by the integration of artificial intelligence (AI). This article explores how AI enhances diagnostics, treatments, and preventive care, highlighting its positive impact on the early detection of diseases and the personalization of interventions. Utilizing advanced techniques such as machine learning and deep learning, personalized medicine greatly benefits from data analysis, leading to more efficient and effective care.