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

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.

Controlling the industrial crystallisation process poses a significant obstacle in the production of drugs and numerous other products. Digitisation of the crystallisation process now allows for radical change by increasing process automation to control overall crystallisation. The main pillars of Pharma 4.0 are process automation, improved control strategies, data visualisation, cloud edge storage, chemometrics, and mathematical modelling technologies. SmartCrys is a revolutionary integrated process control system that harnesses the mainstays of Pharma 4.0 with the combination of PAT tools i

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

Clinical research technology platforms have also emerged, providing participant-facing apps and websites where you can build in or interface with some or all the previously mentioned solutions, as well as expanding to other research-related activities such as virtual training, electronic informed consent form (eICF), participant recruitment, engagement, visit reminders and concierges, etc. Implementing these platforms, the individual participant is given an even more active role in their own research journey, as they are responsible to enter their own subjective data directly into the designa

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),

The pharmaceutical manufacturing process and critical quality attributes (CQAs) are not only needed to control tightly but also required to be protected from any vulnerability in real-time. Currently, pharmaceutical manufacturing companies are facing enormous challenges to protect their plant from possible cyberphysical security (CPS) threats. Cyber-physical security is essential not only to protect the plant from any mechanical damages but also to assure the product quality and thereby, patient safety. The quality of the pharmaceutical products can be improved significantly by implementing a

In August 2021, ransomware operators targeted the health department of the Italian region of Lazio and disabled its COVID-19 vaccination booking system, disrupting the scheduling of new vaccination appointments for days.

Since it contains the city of Rome and is one of Italy’s most densely populated areas, Lazio was an attractive target because of the strong desire among its people to get vaccinated and gain its Green Pass vaccine passport. Hackers likely believed that this would pressure the authorities to pay up the ransom to unlock the systems they had disabled through a cyberattack.

In the last few decades, hot-melt extrusion (HME) has emerged as a rapidly growing technology in the pharmaceutical industry, due to its various advantages over other fabrication routes for drug delivery systems. After the introduction of the ‘quality by design’ (QbD) approach by the Food and Drug Administration (FDA), many research studies have focused on implementing process analytical technology (PAT), including near-infrared (NIR), Raman, and UV–Vis, coupled with various machine learning algorithms, to monitor and control the HME process in real time. This review gives a comprehensive ove

In the treatment of pediatric diseases, mass-produced dosage forms are often not suitable for children. Commercially available medicines are commonly manipulated and mixed with food by caregivers at home, or extemporaneous medications are routinely compounded in the hospital pharmacies to treat hospitalized children. Despite considerable efforts by regulatory agencies, the pediatric population is still exposed to questionable and potentially harmful practices. When designing medicines for children, the ability to fine-tune the dosage while ensuring the safety of the ingredients is of paramoun

The principles of Humane Experimental Technique has resulted in 3Rs concept: Replacement, Reduction and Refinement of animal tests. The number of animals used for both preclinical and quality control is thought to be reduced to zero if vaccines are better characterised while allowing testings by a set of in vitro methods rather than in vivo scenarios. The in vitro methods to detect safety related to potency of vaccines can employ alternative platforms like that of human derived cell/tissue based surrogate systems - The humane technique facilitating increased control of critical stepsin produc

The biopharmaceutical industry operates under strict regulations, and effective supply chain management is crucial for patient safety and timely access to treatments. The biopharmaceutical supply chain is responsible for ensuring efficient and secure delivery of drugs and vaccines while maintaining product quality. Challenges such as compliance, risk management, and technology adoption have emerged in recent years. Cold chain management, monitoring technologies, and new regulations like DSCSA and FMD have impacted the industry. Adhering to trends and regulations, including blockchain and arti

Pharma 4.0, an application of Industry 4.0 concepts in the pharmaceutical industry, aims to enhance manufacturing efficiency, product quality, and consistency. It faces challenges in areas like artificial intelligence, material traceability, optimization, process control, cyber-physical security, and data management due to the complexity involved. However, by incorporating artificial intelligence and advanced model predictive control with robust cyber-physical security measures, predictive capabilities and product quality can be significantly improved. This work focuses on implementing seven

Globally, the outsourcing of services for drug development and commercialisation is increasing. Regulatory services are often included in this, and regulatory activities are increasingly the subject of specific, dedicated FSP (functional services partnership) projects. This article overviews a number of the more common models, including cost models, that can be deployed for the outsourcing of regulatory services. We assessed the appropriate criteria and advantages of these models, illustrating with examples from our experience. Interestingly, over the life of a single project, different model

The Global Biosimilars Market is estimated to reach US$240 billion by 2030, with the Indian market at US$35 billion. The considerable increase in reference products, with the USFDA adding 90 molecules and India approving 70 biosimilars, promises to usher in further growth. The Biopharma industry seems keen on investing in the biosimilar market with a focus on improving healthcare and health care costs for diseases of interest like COVID-19, cancer, immunologic diseases, and diabetes. This is evident in the projected growth of the oncology biosimilar market at 17 per cent CAGR, and the growing