Dassault Systèmes introduced “Emma Twin,” an avatar designed to raise awareness of the key role that virtual twins have in advancing healthcare and the innovations that are shaping the future of medicine.

Through a social media programme, Emma Twin will share stories explaining how the virtual twin of her body was created from anonymous health data to be used for an infinite number of tests that give doctors and researchers a profound understanding of diseases and the effects of new and improved treatments.

Her social media posts will document her participation in ongoing research and medical innovations including:  clinical trials using Medidata solutions; the reaction of her heart to different procedures in the Living Heart project; testing CorNeat Vision’s corneal transplants; epilepsy and Alzheimer’s disease studies in the Living Brain project; wearing the IASO drug administration and monitoring device; and optimizing the home for older adults.  They will also highlight: DAMAE Medical’s portable microscope for detecting skin cancer; Dynocardia’s blood pressure monitoring solution; FEops’ cardiac monitoring; LUCID Implants’ customised facial implants; and the VORTHEx radiotherapy simulation experience.

“Through Emma Twin, we will share stories about the impact of virtual twins on healthcare, in an engaging, meaningful way. Our virtual twins have been used to swiftly develop COVID-19 vaccines, optimise surgical procedures, and provide patients with a greater understanding of treatment options.  By leveraging our pioneering technology, we can draw attention to major healthcare challenges and demonstrate how the virtual world improves outcomes in real life,” said Victoire de Margerie, Vice President, Corporate Equity, Marketing & Communications, Dassault Systèmes.

Virtual twins accelerate the development of solutions to urgent needs for more precise, preventive healthcare by enabling research and health-related disciplines to model, test and treat a human body as precisely, safely and effectively as other industries can with cars, buildings or airplanes.

Emma Twin is the next act in Dassault Systèmes’ “The Only Progress is Human” initiative, dedicated to healthcare and patient experience.  In 2020, the company launched The Only Progress is Human to increase awareness of societal and environmental challenges and inspire the use of virtual worlds to drive sustainable innovations in areas such as urbanisation and water conservation.

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Counterfeit pharma jeopardise patient safety, infringe on intellectual property rights, and undermine the credibility of the pharma industry. Current methods of combating counterfeits are often time-consuming, expensive, and prone to human error.

The recent government announcement that 300 samples would have QR codes has some restrictions. QR codes can be rendered inoperable by scratching them off using a sharp object or marker. It is useless if the QR codes are broken. What use does the label serve, and who is responsible for making sure the QR code is still working when it changes commercial hands? What assurance is there that counterfeiters who can easily mimic a brand’s packaging, name, and logo won’t also be able to mimic its QR codes?

A more efficient and accurate solution is required to identify counterfeit drugs and protect public health.

Combining generative AI and image recognition is probably the answer. With the use of Google Lens and Generative Artificial Intelligence (AI) technology, a complex system for assessing photo metadata (Photo Meta Data) on pharma packaging and verifying the authenticity in real time.

I’d want to make a recommendation for pharma companies, government officials, and customers to combine the strength of AI with picture recognition to create a foolproof way to restrict the risks connected with counterfeit drugs.

*In 2018, Google Images introduced some new features to its image search results. Next to a selected photo, the creator of the image, the credit line, and a copyright notice are immediately displayed. This works by reading the corresponding IPTC photo metadata fields embedded in the image file. On August 31, 2020, this feature was enhanced to also display a licensable badge above an image and a link to the licensing information.

System requirements

a. Generative AI: Implement advanced Generative AI algorithms that analyse visual patterns, text, and packaging features to identify discrepancies between genuine and counterfeit pharma packs.

b. Google lens: Utilise the powerful visual recognition capabilities of Google Lens to capture and interpret codes on the packaging swiftly.

c. Cloud-based database: Establish a cloud-based database containing comprehensive information about authorised pharma products, including packaging details, manufacturing locations, and authorised distributors.

d. Machine learning: Train the system using machine learning techniques to improve accuracy and adaptability over time.

System workflow

1. Generative AI will be used to create unique invisible image tags for each product (like UID). This can be done by training the AI on a dataset of existing batch numbers, allowing it to generate new, unique invisible image tags on brand logo / brand name that cannot be replicated by counterfeiters

2. These unique image tags will then be printed on the packaging of each pharma product during the manufacturing process. (Covertly on Brand Logo and Brand Name)

3. Google Lens will be used by consumers to scan these image tags. Upon scanning, Google Lens will verify the code against a database of legitimate codes (image tags). If the code matches one in the database, the product is confirmed as authentic. If not, the product is flagged as potentially counterfeit.

4. In addition, the system can provide detailed product information, such as manufacturing date, batch number, expiry date, etc., to further assure the consumer of the product’s authenticity.

Key features and benefits

a. Real-time authentication: The system provides instant verification of pharma packs by scanning image tags using Google Lens and analysing visual patterns with Generative AI. This ensures rapid and accurate identification of counterfeit products.

b. User-friendly interface: Develop a user-friendly mobile application or web portal that allows consumers, healthcare professionals, and regulatory authorities to access the system easily and perform authentication checks.

c. Comprehensive database: Maintain a cloud-based database containing detailed information about authorised pharma products, enabling prompt comparison and verification during scanning.

d. Enhanced traceability: Enable pharma companies to track their products throughout the supply chain, reducing the risk of counterfeit products entering the market and facilitating targeted recalls if necessary.

e. Regulatory compliance: Support regulatory authorities in enforcing pharma regulations and combating counterfeit drugs by providing them with a reliable tool for inspections and investigations.

f. Consumer empowerment: Empower consumers to verify the authenticity of pharma products before purchasing, thereby increasing trust in the market and reducing the potential harm caused by counterfeit drugs.

Counterfeit pharma products are a growing global concern. By offering a scalable and reliable solution, our business aims to address the needs of pharma manufacturers, regulators, healthcare professionals, and consumers worldwide. The market potential is substantial, with potential revenue streams including licensing the technology to pharma companies, charging fees for database access, and offering premium services for enhanced features.

By harnessing the power of Generative AI with Google Lens for scanning image tags on pharma packs, proposed solution provides an efficient, accurate, and scalable approach to combating counterfeit pharma products. With enhanced authentication capabilities, regulatory compliance support, and empowered consumers, the solution aims to make a significant impact on public health and safety while fostering trust in the pharma industry.

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One standout aspect of DART is its seamless integration into existing workflows, enhancing end-user engagement

The FDA Modernisation Act 2.0 marks a pivotal moment in reshaping the global pharma and biopharmaceutical industry. Additionally, the Indian DCGI has granted authorization for the use of alternative methods to animal testing, such as cell-based assays and computer models. In alignment with this trend, Transcell and Quantiphi have collaboratively developed an innovative solution known as Digital Animal Replacement Technology (DART).

This advancement harnesses human microphysiological systems and employs artificial intelligence and machine learning-powered digital prediction models. These models are integrated into modular assays that predict safety and efficacy concerns of pharmaceuticals and biopharmaceuticals intended for human use. One standout aspect of DART is its seamless integration into existing workflows, enhancing end-user engagement. This empowers users to assess the safety and efficacy of their assets, providing human-relevant data even before clinical trials commence and sometimes during routine batch testing stages.

Within the developmental cycle of biosimilars, a strategic approach involves a progressive evaluation of biosimilarity and efficacy equivalence. This includes the consideration of conducting animal studies when necessary and appropriate, based on remaining uncertainties. This approach aims to efficiently tailor study requirements.

Hetero Biopharma has embarked on a working relationship with Transcell and Quantiphi to explore the integration of the DART advanced technology into its operational processes.

“We have started working with Hetero Biopharma’s young and dynamic leadership team in offering some of the non-animal DART residing modules for human cardiotoxicity and immunogenicity like key assessments. We are sure to add value in supporting their routine testing requirements within their processes and workflow – Advantage in adopting DART, which is anti-thesis to contract testing model”, says Dr S Dravida, Founder & CEO, Transcell group representing DART implementation opportunity.

Dr Bala Reddy, Director, Hetero Biopharma said, “Evaluating the value of animal studies to support regulatory approval of biosimilars is becoming more and more important. In light of guidelines from various regulatory agencies that encourage alternative approaches to animal testing, innovative technologies like Transcell’s human microphysiological systems in combination with AI & ML-based in-silico modeling, provide opportunities to develop better and more predictive scientific tools to safeguard the environment and the health of both humans and animals.”

Asif Hasan, Co-founder, Quantiphi shared “DART embodies our unwavering commitment to propel bio/pharmaceutical research and development with the utmost ethical standards. Employing ethically sourced human stem cells, a sophisticated digital workstation, and the prowess of artificial intelligence (AI), DART forecasts drug safety, efficacy by analysing human microphysiological systems -drug interactions. DART upholds our vision of sustainable drug discovery, development while maintaining a steadfast focus on ensuring both safety and efficacy.”

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How has the role of decentralised clinical trials (DCTs) evolved in the clinical research industry?

The role of Decentralised Clinical Trials (DCTs) is rapidly evolving within the clinical research industry. While it initially focused on improving patient access to trials, they are now recognised for their immense potential to enhance the efficiency and effectiveness of the entire clinical trial process. This recognition has led to increased adoption and expanded utilisation of DCTs across a wide range of diseases and conditions. The transformation of DCTs within the clinical research industry can be observed through the following developments:

• Enhanced trial data quality: DCTs offer opportunities to collect more accurate and comprehensive data due to real-time, remote patient monitoring and electronic data capture. This improves the overall quality and reliability of the trial data
• Greater focus on patient engagement: DCTs enable greater patient engagement through remote visits, eConsent, and patient-centric technologies. This approach enhances patient participation and retention throughout the trial, leading to more representative and meaningful outcomes
• Broader application: DCTs are now being applied to a wider range of clinical trials, including studies involving rare diseases, complex conditions, and specialised populations. This expansion allows for more inclusive and diverse trial populations

What are the primary reasons behind the increasing traction of DCTs in recent years?

The field of clinical research is currently undergoing a profound transformation fueled by technological advancements, evolving patient expectations, regulatory changes, and lessons learned from the COVID-19 pandemic. These factors are driving key trends and shaping the industry in significant ways. From the integration of digital health technologies to the rise of decentralised trials, these developments are redefining the future of clinical research.

• Advancements in digital technologies: Rapid advancements in digital technologies, such as mobile devices, wearable sensors, electronic health records (EHRs), and telemedicine platforms, have made remote data collection and patient monitoring more feasible
• Patient-centric approach: DCTs prioritise the convenience and comfort of participants. By allowing them to participate in trials from their homes or local communities, DCTs remove geographical barriers and reduce the burden of travel and site visits
• Broader recruitment potential: Traditional clinical trials often face challenges in patient recruitment, leading to delays and increased costs. DCTs have the potential to overcome these challenges by expanding the recruitment pool beyond the limited geographic area close to trial sites. By including participants from remote areas, DCTs enhance diversity in study populations and improve the generalisability of results
• Regulatory acceptance and guidelines: Regulatory agencies, recognising the benefits of DCTs, have issued guidelines to support their implementation. For example, the FDA and the EMA have released instructions on decentralised trials, providing recommendations on data integrity, patient privacy, remote consent, and other considerations. These guidelines have fostered confidence among sponsors and investigators, facilitating the wider adoption of DCTs
• Learnings from the COVID-19 pandemic: The COVID-19 pandemic accelerated the adoption of remote approaches in clinical trials. With travel restrictions and safety concerns, traditional trial operations faced significant disruptions. DCTs emerged as a viable alternative, enabling researchers to continue studies remotely. The successful implementation of DCTs during the pandemic has highlighted their potential and paved the way for their continued use even beyond the pandemic

 What are the key benefits and advantages of conducting decentralised clinical trials compared to traditional site-based trials?

Revolutionising clinical research, DCTs have surfaced and presented unparalleled benefits that disrupt traditional approaches. It has demonstrated numerous advantages such as:

• Improved patient access and convenience: DCTs offer heightened accessibility and convenience by cutting down on the frequency of travel to clinical trial sites
• Enhanced patient retention: Maintaining patient retention in clinical trials is a frequent obstacle, often arising from demanding visit schedules, travel obligations, and logistical complexities. DCTs address these challenges by offering a patient-centric experience that alleviates these burdens
• Cost and time efficiency: DCTs achieve cost-minimisation in operations by doing away with the requirement for physical trial sites and decreasing on-site monitoring
• Real-time data collection and analysis: By enabling real-time data collection and prompt analysis, researchers are equipped to make informed decisions during the trial, leading to the development of more efficient and adaptive protocols
• Refined data quality and analysis: Enhanced data accuracy allows researchers to conclude the study findings with confidence, leading to the establishment of trust and credibility within the research community
• Driving flexibility and adaptability: Thanks to the remote nature of these trials, adjustments can be seamlessly implemented, encompassing the enlargement of the participant pool, modifications to study parameters, and timely responses to external factors like pandemics or natural disasters

 How does the use of technology enable remote patient monitoring and data collection in DCTs?

The use of technology plays a critical role in enabling remote patient monitoring and data collection in DCTs. Through digital health tools such as mobile applications, wearable devices, and connected sensors, participants can track and transmit real-time health data from their homes. EHRs facilitate securing the sharing of patient information between healthcare providers and trial sponsors.

Additionally, telemedicine platforms make it easier for people to have virtual consultations instead of in-person appointments. With remote data capture tools like electronic case report forms (eCRFs) and electronic patient-reported outcome (ePRO) systems, participants can directly enter their data and responses into digital forms. By integrating data from various sources like wearable devices and EHRs, valuable insights can be derived through real-time analysis. Measures are taken to ensure secure data transmission and maintain privacy to protect participants’ information. In essence, the integration of technology in DCTs enhances participant convenience, improves data quality, and optimises trial operations through remote monitoring and data collection.

 How do DCTs improve patient recruitment and retention compared to traditional trials?

DCTs expand participant accessibility by allowing individuals to engage in trials from their homes or local communities, eliminating geographical barriers. This broader reach increases the potential participant pool and enhances diversity in study populations. Additionally, the convenience of participating remotely reduces the burden on participants, resulting in higher engagement and improved retention rates. By minimising the need for frequent in-person visits and associated travel costs, DCTs enhance convenience and reduce the logistical challenges that often deter participation or lead to participant dropouts in traditional trials. The flexibility and patient-centric nature of DCTs contribute to increased recruitment rates and better participant retention throughout the trial, ultimately leading to more successful and efficient clinical research.

Additionally, the integration of applications with remote sensor devices allows subjects to virtually record trial-related details, eliminating the need for site visits. The ‘televisits’ feature enables subjects to conveniently engage in discussions with site clinicians, addressing their day-to-day questions and concerns. With the ‘caregiver concept’, patients can grant authorisation for a caregiver to provide their details when direct communication with the site is not feasible. In contrast, web portals provide a convenient solution, allowing patients to remotely log in, complete questionnaires, and record study-related information without the requirement of visiting the site in person. These features enhance accessibility and streamline the participation process in clinical trials.

 What are the future trends and potential advancements in decentralised clinical trials that are being explored?

The field of clinical trials is experiencing a paradigm shift with the emergence of DCTs. These trials leverage innovative technologies and approaches to enhance participant engagement, streamline data collection, and optimise trial design. As the industry progresses, several anticipated advancements will shape the future of DCTs.

• Decentralised trial designs: Further exploration of hybrid trial designs that combine aspects of traditional and decentralised models is anticipated. These designs can optimise the balance between in-person visits for specific procedures and remote data collection, tailoring the trial design to the specific needs of the study
• Virtual Health Assistants: VHAs play a vital role in DCTs by delivering personalised guidance, remotely monitoring participants’ health, ensuring medication adherence, facilitating communication, and enhancing participant engagement.  They educate participants on trial protocols, remotely collect real-time health data, promote medication adherence, address queries, offer emotional support, and maintain secure communication channels, contributing to the success of DCTs.
• Wearable and remote monitoring devices: Advancements in wearable technology, such as biosensors and remote monitoring devices, are expected to play a significant role in DCTs. These devices can collect real-time physiological data, allowing for continuous monitoring of participants’ health status and treatment response
• Generative AI: Generative AI has the potential to analyse large datasets generated by DCTs, identify patterns, predicted outcomes, and provide personalised insights. Furthermore, the technology can also assist in generating synthetic data to enhance datasets
• Blockchain technology: Blockchain technology holds promise for enhancing data security, privacy, and integrity in DCTs. It can enable secure data sharing, transparent consent management, and audit trails, ensuring trust and compliance in the trial process
• Regulatory advancements: Regulatory agencies are actively working on evolving guidelines and frameworks to support the implementation of DCTs. Continued collaboration and advancements in regulatory policies can further promote the adoption and acceptance of DCTs in the industry.

viveka.r@expressindia.com 

viveka.roy3@gmail.com

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 Indegene, a digital-first, life sciences commercialisation company announced the launch of metaverse capabilities to support life sciences organisations with a variety of use cases, including health care provider (HCP) interactions, HCP education, and patient education.

A statement from the company said, “Indegene’s domain expertise will provide life sciences organidations a foundation for navigating the complexity of this emerging technology and the flexibility to create tailored virtual worlds. Using these, life sciences organizations can foster immersive healthcare experiences, like interactions with HCPs in a virtual medical congress, meeting for a virtual educational lecture, or facilitating interactions in a virtual patient hub.”

“Life sciences organisations are looking to reimagine healthcare interactions and be ahead of the curve. Providing new ways to connect, educate, and lead transformation using virtual and augmented reality can help solve some of their key business challenges. We are excited to bring to our clients the ability to create immersive experiences to aid seamless and richer engagements with HCPs and patients. Indegene’s metaverse capabilities to design highly personalised virtual worlds, coupled with our experience and deep domain expertise, enables life sciences companies to be future ready,” said Gaurav Kapoor, Executive Vice President, Indegene.

“Metaverse has the potential to be a game changer in the education industry. Its intrinsic nature opens the door for a new dimension of how knowledge can be shared and measured”, said, Gustavo Kesselring, Vice President, External Affairs, at IFAPP Academy. “In the near future, its gamification features can be used to transform the way we have taught and evaluated for more than a hundred years, and the early adopters will benefit the most.”

Indegene is a member of the Metaverse Standards Forum, a cross-industry forum designed to foster cooperation and interoperability standards for an open metaverse.

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Partnership to integrate Qure.ai’s smart artificial intelligent technology to detect lung cancer early on

India-Sweden healthcare Innovation Centre and its knowledge partner AstraZeneca India collaborated with the Directorate of Health Services (DHS) Jammu to integrate Qure.ai’s smart artificial intelligent technology to detect lung cancer early on.

Under the aegis of Indo Sweden Healthcare Innovation Centre (ISHIC), Qure.ai is scaling-up the integration of its AI-powered chest x-ray interpretation tool that can benefit early and easy detection of lung diseases including lung cancer.

Cecilia Oskarsson, Swedish Trade Commissioner to India said, “We are delighted to initiate this first project in Jammu towards early screening and diagnosis of lung diseases in the state. We look forward to supporting the start-up ecosystem and the states towards building an innovative ecosystem in the country.”

Dr Sanjeev Panchal, Country President and Managing Director, AstraZeneca India said, “We celebrate the progress that has been made in cancer care, including advances in screening, the development of innovative therapies, greater public-private collaboration and increased prioritisation of health equity. As a global cancer community, we have many reasons to be optimistic about the future. We are moving ever closer to achieving our ambition eliminating cancer as a cause of death.”

Prashant Warier, CEO, Qure.ai said, “AstraZeneca has helped us spread our offering across the world that has led to approximately 170,000 scans in 25 countries, with high malignancy risk lung nodules identified in 1.6 per cent of scans. Today we are tapping further into technology to enable faster diagnosis and speedy treatments.”

The AI powered chest X-ray is designed to distinguish lung nodules in under a minute and minimise the chances of lung cancers going undetected. Importantly, this tool is being accessed in primary care setting where x-rays are utilised most commonly.

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The contemporary drug repurposing techniques using advanced artificial intelligence (AI) are gaining traction in the pharma industry to not only minimise the cost and time but also to bring down the risk in the process of retargeting drugs for viral and other rare diseases, says GlobalData.

Kiran Raj, Practice Head of Disruptive Tech at GlobalData, comments, “The pharma industry has seen AI-augmented approaches to repurpose drugs against COVID-19 infections like Eli Lilly’s Olumiant, which further increases the strategic collaboration appetite of pharma companies to develop computational approaches that can de-risk the systematic identification of drug repurposing leads.”

Abhishek Paul Choudhury, Senior Disruptive Tech Analyst at GlobalData, comments, “AI is advancing drug repurposing by mining huge biomedical datasets for hidden patterns and evidence. This can maximise the drug asset values as the technology analyses massive amounts of data to find the existing drugs used to treat other conditions by developing a specific treatment for an underserved disease or a particular indication.”

The Innovation Explorer database of GlobalData’s Disruptor Intelligence Center highlights the key company collaborations in pharma to advance AI-powered drug repurposing techniques.

In January 2023, US-based companies Medable and Every Cure partnered to use drug repurposing to accelerate the discovery of treatments for rare diseases such as aromatic l-amino acid decarboxylase (AADC) deficiency. The duo aims to identify novel use cases with Medable’s specialised software and services as Every Cure plans to scale up an innovative treatment to find therapies for around 9,000 disorders, many of which have no federally approved treatment.

In April 2022, Geneva’s DNDi made a non-commercial collaboration with London’s BenevolentAI to formulate a list of potential biological targets (proteins that can be targeted by a potential drug) and drug repurposing candidates that could de-escalate the severity of dengue infection. The project intends to combine BenevolentAI’s drug discovery platform with DNDi’s acumen and global network of dengue partners to enable researchers to decode insights that human reasoning alone would not have been able to uncover.

In February 2022, UK’s Healx obtained exclusive license rights from NY-based Ovid Therapeutics to investigate gaboxadol, also known as 4,5,6,7 tetrahydroisoxazolo(5,4-c)pyridin-3-ol (THIP), as part of potential combination therapy for Fragile X syndrome, as well as a treatment for other indications. Healx, according to the agreement, will find an optimal treatment for the condition by combining gaboxadol with other compounds identified by the Healnet AI platform, including HLX-0201.

Choudhury concludes, “Drug repurposing is becoming increasingly popular as AI advances to offer new insights into disease drug targets while increasing the success rate of clinical development trials. The process will eventually provide patients with faster access to new treatments and answers to rare disease symptoms, thereby potentially saving lives.”

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The pharma industry is one of the world’s most consistently growing industries. Pharma companies are bound by a multitude of regulations and standards. Implementing innovation in this fast-growing industry faces numerous challenges every day in terms of safety, traceability, and data availability. Today’s pharma companies face significant manufacturing challenges, including standards compliance and traceability to detect errors immediately. To meet these requirements, many pharma companies rely on a well-established approach: SCADA systems.

Today, a new generation of requirements has pharma companies looking for new solutions. Data acquisition is no longer enough, and factories are demanding faster and more accurate solutions with capabilities for energy monitoring, condition-based predictive maintenance, MES/ERP connectivity, reporting, and advanced analytics. In today’s fast-growing industry, large corporations are looking for a single-source solution and an integrated approach to leverage existing capabilities, and be ready for the future.

Data-driven SCADA system

Data is the new science. The world is now awash in data, which helps consumer needs be identified more accurately. Industries are looking for techniques and solutions to analyse data easily, quickly, and securely. To do this, they need a system that combines all the little data into one process. Futuristic manufacturing techniques are the hallmark of an excellent pharma facility. The pharma industry thrives on integrating such systems and techniques into its operations. SCADA represents one of the most significant advancements of the past and has helped shape today’s manufacturing industry.

The pharmaceutical industry has realised the importance of this system that allows them to analyse, implement and identify errors if they find any. Pharma companies spend a large portion of their revenue on protecting their data. Despite the market being flooded with various SCADA systems, they are looking for a secure network system. B&R India, a leading manufacturer of industrial products and a reliable partner, has recognised the security gap in the pharmaceutical industry. That’s why they have packaged important innovations for the pharmaceutical industry in a solution called PharmaEdge. This system supports FDA compliance and 21 CFR Part 11 and is aligned with the needs of Industry 4.0.

Solution built just for pharma

To meet the demands of the pharma industry, B&R has developed an integrated single-PC solution for monitoring and controlling the entire operational process that also meets the increasing requirements of FDA compliance, one of the fundamental benchmarks for pharma manufacturers. PharmaEdge offers all the benefits of SCADA and a robust control system in one device. In short, it is a one-stop solution with the ability to add energy monitoring, condition-based predictive maintenance, and MES/ERP connectivity. It also enables the implementation of smart machines for the future of the industry. The integrated PharmaEdge solution helps users optimize the performance of their automation systems while improving cost and energy efficiency. Instead of using separate control systems for process control, SCADA, energy monitoring and condition monitoring, users get all these functions in a single integrated system with built-in cybersecurity. With this innovative one-box solution, users in factories can monitor and control their entire operation with a single system.

The unique PharmaEdge solution consists of a B&R industrial PC running a hypervisor solution with Linux and B&R’s real-time operating system, providing easy access to machine and process automation libraries for easy configuration. There are no restrictions on internal tags and no incremental costs for additional tags. The PharmaEdge solution’s built-in features support easy reporting and historical data retrieval. Several additional features such as access protection, protected data archiving and retrieval, electronic signature, easy batch reporting, user-friendly audit trail and change management, to name a few, make this solution even more trustworthy. The PharmaEdge solution is OPC-enabled with seamless connectivity to MES/ERP/EBMR and easy cloud connectivity via MQTT. It also has simplified dashboards for easy data analysis. It is compatible with standard browsers or mobile devices and consists of iOS and Android apps that provide access to dashboards and reports. This solution is user-friendly and easy to use and is designed primarily for the challenges faced by pharma companies.

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Digitalisation and emerging technologies have revolutionised the pharma industry. These technologies are very useful from the perspectives of quality and compliance, based upon Industry 4.0/Pharma 4.0 concepts. 

Robotic Process Automation (RPA) and Artificial Intelligence (AI) are no longer small operations as manufacturers are using these technologies to maximise quality and compliance. Many companies are already using AI to analyse huge scientific data in an effort to speed up and improve the drug discovery process. 

These technologies have new applications in diverse areas like regulatory/compliance, clinical trials, manufacturing, and supply chain. RPA automatically handles manual, repetitive, time-consuming, and highly structured tasks such as data entry, reviews and back-office functions. RPA solutions can improve regulatory compliance because bots do not deviate from programmed steps and audit trail history can be tracked. They provide comprehensive, unchangeable, and time-stamped activity logs, reducing risks and errors through the automatic execution of repetitive and routine manual activities. 

There are several applications of RPA/AI in the pharma industry from quality and compliance perspectives such as:

Data integrity compliance: Achieved through RPA audit trails review of various chromatography data generated during laboratory analysis. When reviews performed with RPA detect no anomalies, the reviews can autonomously be closed and logged by the bot. However, if the bot detects any inconsistency or discrepancy that requires human evaluation, RPA can be programmed to report the issue to one or more users before proceeding with the next steps of the process. 

Ensuring quality, predictive quality analytics (PQA): AI-enabled LIMS–QMS, automates time-consuming, error-prone, manual inspection tasks. Predicting the quality of a batch is another big advantage of newer technologies as they help to standardise quality monitoring processes. They analyse data, predict quality, deal with complaints handling process and make remedial suggestions to mitigate the risk of failure of a batch.

Clinical trials: AI and RPA are used to speed up the process of selecting the volunteers saving time from months to only a few days. AI is now being used in identifying the right candidate for clinical trials. Monitoring the pharmacovigilance activity is another area where RPA is of great advantage. It helps to monitor huge amounts of adverse event data, as well as enable necessary communications to report and accumulate such data. RPA solution utilises bots to substantially reduce data processing time, improve reliability and mitigate risk by eliminating errors and improving accuracy in trial documentation.

The regulatory documents submission process is a huge and time-consuming activity where RPA solutions can speed up certain required activities, such as document status tracking and creating a records dossier, thereby reducing process time.

Manufacturing: AI helps to reduce manual oversight in manufacturing and allows tighter control of quality and operating costs by assessing manufacturing data from multiple batches and product lines, identifying process anomalies and predicting quality issues. This can direct staff to investigate only those batches most likely to have quality issues, saving time and resources. It proactively identifies anomalies, prioritises compliance risks, and improves operational efficiency.

Sterile manufacturing: The applications in pharma manufacturing are vast, including aseptic roller bottle processing, multi-format aseptic filling, aseptic cytotoxic compounding, packaging, warehousing and distribution. Robotic production lines that can provide flexible aseptic filling and closing of ready-to-use vials, syringes, and cartridges with a single machine, resulting in overall production speed are necessary to remain competitive and cost-effective. Several benefits in sterile manufacturing like minimising human errors (like foreign matter, hair etc. contaminations), maintaining air velocity, and sterile conditions in core areas, RPA enables closed systems to eliminate all sources of contaminations.

Predictive maintenance: Maintenance is simpler due to fewer parts, and if done properly, can result in significantly longer lifespans. Robots facilitate ongoing maintenance by self-monitoring and using programmed alarm scenarios to alert operators of issues. AI is being used to predict the failure of equipment in the near future. As soon as an alarm is known, preventive actions start, thus ensuring zero downtime.

Packaging operations: Robotic automation is being used in packaging operations to minimise defects by way of in-line checks along with several cameras for separating defective tablets, capsules, empty strips pockets, defective blisters etc.

AI is being used in R&D drug discovery, clinical trials, manufacturing, quality control laboratory and supply chain. Automation is already transforming the pharma industry in areas like product development and real-time monitoring. Many companies are increasingly turning to robotic process automation as a solution allowing them to enhance productivity, quality, operational efficiency, and customer satisfaction. Overall, AI and robotics operations are a boon to the pharma industry in ensuring speed of product availability, quality, safety and efficacy of the products in the interest of patients. Pharma operations will be completely AI-enabled, AR + VR towards paperless plants in near future.

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Artificial Intelligence (AI) and Big Data will be the two most impactful technologies for the pharmaceutical industry for the fourth year in a row in 2023, according to a survey by GlobalData. The company notes that 39 per cent of healthcare industry professionals in the survey believed that AI would be the emerging technology bringing the greatest impact on the pharma industry in 2023, followed by Big Data with 27 per cent of the selection.

GlobalData’s latest report, ‘The State of the Biopharmaceutical Industry – 2023’, reveals that AI and Big Data were trending as the two most disruptive emerging technologies since 2020, with a significant margin from the third choice in all four years.

Elton Kwok, Market Research Manager in Pharma at GlobalData, comments, “Drug-developing and other processes are complex and highly structured in the pharma industry. The processes generate a vast amount of data, especially in the current digital age; however, this data can be useless or meaningless if it is not properly analysed. AI not only can help process the data more efficiently, saving time and labour cost; it can also produce analysis more accurately since it feeds on high-quality data, which comes from the proprietary datasets.”

Kwok concludes, “It might take some time for AI and Big Data to display their true power, but the two technologies together are expected to play an important role in the industry, in terms of optimising the entire pharma value chain. This powerful duo can be applied to optimise a wide range of processes, from drug design to end-user reach.”

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