Seoochre

Artificial Intelligence (AI) and machine learning-based technologies have the potential to transform healthcare because they offer new and important insights derived from the vast amount of data generated during the delivery of healthcare every day. The capacity of AI to learn from real-world feedback and improve its performance makes this technology uniquely suited as Software as a Medical Device (SaMD) and is responsible for it being a rapidly expanding area of research and development. Clinical pharmacy practice may undergo major change due to the implementation of this technology. The cha

However, these efforts are haunted by a shortage of resources, restrictions on importing API, social distancing at facilities, disturbed supply chains, and tremendous pressure to quickly manufacture and distribute products. Despite these arduous circumstances, it remains critical for pharma companies to maintain quality and compliance and follow regulatory guidelines. Doing so requires pertinent measures to ensure adherence to Current Good Manufacturing Practice (CGMP) guidelines, and data integrity to meet the requirements of regulators including the U.S. Food and Drug Administration (FDA),

Biologics are basically the products which are developed and produced from living organisms like human, plant or animal cells and, of course, microorganisms (bacteria, yeast, etc.). Having no definite structure, biologics are large and complex molecules which undergo sophisticated procedures while being developed and manufactured. Monoclonal antibodies, hormones, enzymes, insulin, etc. can be referred to as biologics.

Generics are simple molecules and exact copies of approved brand drugs. Contrary to biologics, generics are easier to synthesize, purify and manufacture. Drugs such as phenyt

Cancer drug resistance is complex phenomenon and can be categorised as intrinsic or acquired resistance. In few cases, cancer cells survive even at the clinically relevant doses of established standard chemotherapy which is called as intrinsic resistance whereas at some instances after attaining promising result at initial phases, therapy suddenly turns out to be non-responsive and leads to recurrence of tumour growth. This acquired drug resistance often called as Multi Drug Resistance (MDR) when cancerous cells develop resistance and cross resistance to functionally or even structurally unre

Soft gels, also known as soft capsules or soft caps, are a highly popular pharmaceutical and nutraceutical dosage form, with around 2,500 units consumed every second globally. A forecast by HJR Research predicts a CAGR of 5.5 per cent over the next decade, with the global market value expected to reach $756 billion by 2025. During the same period, the Asia-Pacific region is projected to be the fastest-growing market at a CAGR of 6 per cent, in terms of value. Driven by the increasing popularity of nutraceuticals, where clean label and comfort in swallowing are key factors in customer buying d

Using big data to design clinical trials better and predict outcomes can make it commercially feasible to develop drugs for smaller patient populations. Pharmaceutical companies are looking to big data to reduce costs in research and development and manufacturing. With the explosion of health-related data in recent years, the market for artificial intelligence in drug development, valued at US$200 million in 2015, ballooned to US$700 million in 2018 and is predicted to appreciate more than US$5 billion in 2024, according to a report by big data analytics. Artificial Intelligence (AI) and big

Biopharma’s efforts to digitally transform operations are proving more important than ever to drive improvements in process efficiency and deliver essential treatments to patients. However, the industry’s attempts are returning mixed results and the digital transformations of many enterprises remain in early-phase development. As with any business initiative, a lack of clear goals and strategies keeps some biopharma programs from being successful. As a result, these shortfalls may be further preventing many companies from moving toward the more data-driven future the industry needs to deliver

To bring this into reality, pharmaceutical PV organisations need to move into a “digitalised future” where technology plays a key role in PV processes. This includes automating and streamlining the information streams to reduce complexity, from case processing to reporting. Once automated, companies need to begin to look to artificial intelligence to add further value from their data.

By applying artificial intelligence (AI) and data science approaches, organisations can turn the overabundance of data from being a challenge to solve, into an opportunity. A well-designed, automated, AI-powe

There's a need consolidate natural information with computational strategies for extricating important and fitting qualities from the thousands of qualities measured. Artificial Intelligence (AI) has been connected within the sedate disclosure field for decades. Today, conventional machinelearning modelling has advanced into an assortment of unused strategies, such as combi-QSAR and crossover QSAR, and remains a prevalent approach to consider different drug-related themes. There are different drugs on the showcase and/or in clinical trials that have been outlined by computational strategies.

One of the main issues faced by the pharmaceutical industry is ensuring reliable and timely access to secure, innovative, and economical medication. These issues are becoming more critical due to the world's growing but ageing population. Recent scientific developments in the healthcare market have given rise to targeted medicines that have now opened up new treatment options for individuals according to their lifestyle and genetic makeup. These developments have led to a shift within the market towards the improvement of lower dosage and extremely powerful drug products. Ultimately, these tr

Artificial Intelligence (AI) and machine learning-based technologies have the potential to transform healthcare because they offer new and important insights derived from the vast amount of data generated during the delivery of healthcare every day. The capacity of AI to learn from real-world feedback and improve its performance makes this technology uniquely suited as Software as a Medical Device (SaMD) and is responsible for it being a rapidly expanding area of research and development. Clinical pharmacy practice may undergo major change due to the implementation of this technology. The cha

The recent pandemic served as a significant catalyst to enable even more research tasks to fit in to a digital or decentralised solution. These activities likely would have progressed to a digital and decentralised layout over time as technology, legislation and industry acceptance underpin the change. Among these tasks, consenting to participate in clinical research was included in the “e-club” (e.g., eConsent/eSignature, eCOA, etc.) across most countries. Adoption of televisits was equally promoted and implemented to overcome the logistics of missing visits during lockdowns in addition to

This article explores the profound impact of bioinformatics in the realm of precision oncology, revolutionising the understanding, diagnosis, and treatment of cancer. Bioinformatics, a multidisciplinary field, bridges the gap between vast biological datasets and meaningful insights, enabling personalised therapies and groundbreaking discoveries. However, challenges in data integrity, reproducibility, and infrastructure must be overcome to fully realise it’s potential. Bioinformatics stands as a beacon of hope

India is rapidly emerging as a global hub for clinical research, with many international pharmaceutical companies and research organisations choosing the country as a site for their clinical trials. However, the majority of clinical research is conducted in Tier-1 cities such as Mumbai, Delhi, and Bangalore, with much less attention paid to Tier-2 and Tier-3 cities in South India.

There are several reasons why Tier-2 and Tier-3 cities in South India are not included in clinical research. One of the main reasons is the lack of infrastructure and resources required for conducting clinical tr

While traditional vaccine modalities continue to play an important role, 87% of the respondents intend to focus on mRNA and the majority believe this modality will dominate the future vaccine landscape. Most manufacturers stated an intent to establish capabilities in novel vaccine platforms and indicated that both traditional and modern cell-based vaccines remain important given their proven regulatory record, high efficacy, and generally fewer side effects.

Given the protection offered by the SARS-CoV-2 mRNA vaccines and the accelerated development timelines, it’s no surprise that this mo

Cancer is considered as a common name to address a large group comprising more than 100 diseases affecting several parts of the body. All cancers show common characteristics such as the uncontrolled growth and proliferation of abnormal cells, infiltrating and spreading to different tissues and organs throughout the body, and destroying the normal cells and tissues. Cancer can begin in the epithelial tissue and is known as carcinomas, and when it begins in the connective or supportive tissue, they are called sarcomas. The blood cancers are known as leukemias, and when it begins in the plasma c

Medicine is the testament to the virtue of human innovation - a collective desire to reduce the burden of disease and an ever evolving journey to enhance the quality of human health. The origin of medicines can be traced back to ancient times when human began to use the natural resources to treat injuries and illness. Highly developed and documented evidences of medicinal practices comes from the world’s most ancient civilisations such as Egypt, India, China and Greece1. Traditional Chinese medicine2, which dates back more than 2,500 years, used a combination of herbs, acupuncture, and other

Artificial intelligence is a field of engineering and science that focus on making intelligent machines. Artificial intelligence is a top technology that is reshaping the pharmaceutical industry's future. For ages, the pharmaceutical industry has been developing cures and treatments. Traditionally, medication design and manufacture took many years, extensive clinical studies, and sky-high prices.This has been changing with the advancement of 21st-century technology. We will see different drug designs, manufacturing, and clinical trials in the future.

Natural Language Processing (NLP), Mach

Decentralized clinical trials (DCTs) leads with a premise to leverage technology to transform the traditional clinical trials model. Incorporating digital tools, telemedicine, and real-world data, DCTs enhance flexibility, accessibility, and participant-centricity. Such a promising alternative addresses inefficiencies, high costs, and limited diversity, revolutionizing the landscape of medical research.

Traditional clinical trials have long served as the cornerstone of medical research, providing essential evidence for evaluating the safety and efficacy of new interventions. However, these

Quantum computing is a field that uses quantum mechanics to solve complex problems faster than classical computers. It emerged in the 1980s when it was discovered that certain computational problems could be tackled more efficiently with quantum algorithms than with their classical counterparts. Unlike classical computers that use bits, which can only be 1 or 0, quantum computing involves qubits that can exist in a multidimensional state. The power of quantum computers grows exponentially with more qubits, while classical computers that add more bits can increase power only linearly. Quantum