• iCM | iQM

Xcelpros

A Global technology and consulting services
Artificial intelligence in the biotechnology 5 key trends banner
  • Xcelpros Team
  • No Comments

Artificial Intelligence in the Biotechnology – 5 Key Trends
Artificial Intelligence in the Biotechnology – 5 Key Trends 700 500 Xcelpros Team

At a Glance

  • The biotech industry is witnessing unprecedented demand on many fronts. Companies are looking to invest in fast-paced innovation, systematic storage of massive research data, analysis of humongous databases, and meticulous management of the business processes. AI-enabled applications play a crucial role in meeting these demands.
  • Machine learning, robotics, informatics, and AI branches can help in expanding the horizons of the biotechnology industry and move towards newer possibilities.

AI-led Transformation of the Biotech Industry and Its Positive Effects

The Biotechnology industry is currently relying heavily on storage, filtration, analysis, and the exchange of data. Massive databases are maintained by biotechnology companies and various health organizations worldwide. Drug manufacturing, chemical analysis of different compounds, sequencing of RNA and DNA, enzyme studies, and other similar biological processes require the strong support of computerized tools and applications to gain pace and reduce manual errors.

Today, the world is witnessing an unprecedented health emergency in terms of the Coronavirus pandemic. Economies are collapsing, countries are under lockdown, and all hopes are pinned on the biotechnology industry to come up with a safe, effective vaccine in the shortest possible time frame. The use of Artificial Intelligence in biotechnology and related applications play a crucial role in managing biological processes, boosting medicine production, handling supply chains, and taking care of the pool of data for this industry.

Increased and better predictability for both structured and unstructured data helps companies in planning their operations accordingly for enhanced productivity and a faster pace of work.

Figure 1Applications of Artificial Intelligence in Different Fields of Biotechnology

Applications of Artificial Intelligence in Different Fields of Biotechnology artwork

Leading biotech companies are investing in advanced AI tools to:

  • Analyze research data
  • Accelerate vaccine development
  • Classify the target market and demographic
  • Identify the right ingredient to produce the vaccine

86%of current or planned AI spending is in customer-oriented areas, with marketing and sales leading the pack

 

$1.2 TNestimated additional revenue/ shifting revenue driven by AI in three years

 

While there are still many unknowns when it comes to a successful coronavirus vaccine, this US biotech firm has applied artificial intelligence to accelerate the process of vaccine development.

The biotechnology sector will leverage artificial intelligence and its related applications with vigor in the coming years. According to an article for Medium by Melanie Matheu, Ph.D., the next generation of therapeutics entering drug pipelines will contain targets selected by AI screening, likely improving the 86% clinical trial failure rates for small molecules.

The biotechnology industry has various sub-sectors ranging from human life sciences, food industry, agricultural biotechnology, animal biotechnology, and industrial applications. These branches can all leverage the advancements seen in artificial intelligence and machine learning related applications developed in the past decade, including five key AI trends that will transform the biotechnology industry, listed below.

The Application of AI is Shifting More Towards Knowledge Workers

79%agree AI and related technologies are having a transformational impact on workflows and tools for knowledge workers

 

80% say that placing powerful AI-fueled application in the hands of knowledge workers is critical to productivity and performance

 

84% agree AI streamlines processes, freeing knowledge workers for move creative, intuitive and laterally thinking activities

 

Source: Microsoft

01Boosting Innovations: From Lab to the Market

The past decade has witnessed the need for fast-tracked innovation, production and deployment of medicines, industrial chemicals, food-grade chemicals, and other biochemistry-related raw material. AI in Biotech plays a crucial role in boosting innovation not only in the laboratories but also throughout the lifecycle of a medicine or chemical compound (right to the point where it reaches the market). Based on the target market, AI-based tools and applications help in developing the structure of molecules. Machine learning, a subset of artificial intelligence, helps in calculating permutations and combinations of various chemicals to know the right combination, without having to perform the experiments in the lab through manual processes. The use of artificial intelligence in biotechnology is bringing innovations that can help in predictive analysis to forecast the demand for a particular medicine or a chemical in the market. AI in Biotech can also help in managing the smart distribution of the raw material required by the biotechnology industry through the use of cloud computing.

Figure 2Functionalities of AI in Biotech Industry

Functionalities of AI in Biotech Industry

02Open Source AI Platforms: Faster Data Analysis

Scientists across the globe are looking at AI programs that can take over the tedious nature of data maintenance and data analysis. Tasks like gene editing, enzyme compositions, chemical studies, and such crucial informatics are analyzed systematically for faster and more accurate results. Open-source AI programs such as CRISPR libraries and H2O.ai are playing an essential role on this front by relieving lab assistants of repetitive tasks like data entries and analysis. By eliminating manual functions for healthcare providers and scientists, they can better focus their efforts on innovation-driven processes and it will be possible with the use of artificial intelligence in biotechnology.

03Pushing the Boundaries of Agricultural Biotechnology: Increasing Quality and Quantity

Biotechnology plays a crucial role in genetically modifying plants to develop more and better crops. AI-based tools become essential to this process of genetic modification to study the features of the crop, to note down and compare qualities, and to forecast plausible yield. Apart from these tools, robotics, an arm of artificial intelligence, is being used by the agricultural biotechnology industry for packaging, harvesting, and other essential tasks. AI in biotech also helps in planning the upcoming patterns in the movement of material by combining weather forecasts, data on the nature of farmlands, and the availability of seeds, manure, and pesticides.

04Discovery of New Drugs and Vaccines: Shrinking the Timeline

In a globalized world, newer diseases have a fast way to spread across continents. Thus, the biotechnology industry is at a race against time to develop newer drugs and vaccines to be able to contain such diseases. Artificial intelligence and machine learning are vital in speeding up the process of recognizing the right molecules, helping in synthesizing them in the labs, data analysis for efficacy, and it supplies to the market. Operations, which would usually take 5-10 years, have now been shrunk to 2-3 years with the use of artificial intelligence in biotechnology.

Figure 3Subsets of Artificial Intelligence in Biotechnology

Subsets of Artificial Intelligence in Biotechnology

05Facilitating Global Connect: Sharing Biotechnology Developments Worldwide

AI platforms are resourceful in letting scientists across the globe have access to imperial data regarding newer medicines and other industrial developments. Many machine learning tools are assisting scientists in decoding data and understanding patterns of a particular disease in a far-away country and utilizing it to build analytical models for their geography. The accuracy of scientific models has increased by several folds, after the introduction of AI in Biotech.

While these are the key trends, AI and related tools are helping in transforming the biotechnology industry in many ways. Coming times will see the use of artificial intelligence in biotechnology for the betterment of humankind by the progress it facilitates in the fields of biosciences and technologies.

The power of integration of Microsoft’s AI with Microsoft Dynamics 365 helps biotech companies get over the industry’s pressing challenges. Hindrances such as resource management, stringent regulations, quality management, etc., and establishes seamless workflow by ensuring unified data sharing, visibility, and connectivity across diverse channels and operations so that teams better communicate.

This collaboration with the use of artificial intelligence in biotechnology helps your company to

  • Achieve regulatory compliance
  • Gain visibility into your supply chain management
  • Track and control your inventory with accuracy, and
  • Integrate industry best practices for corrective and preventive action

Finally, the digital transformation achieved with the Full Microsoft Suite gives you data in real-time to make smart and actionable business decisions to spur company growth.

Key Takeaways

  • The biotechnology industry has progressed significantly with the application of AI and related computerized tools.
  • Be it medical, industrial or agricultural biotechnology, AI, machine learning, and robotics play critical roles in pushing the boundaries of possibilities in these fields.

Using our years of industry experience in the biotech, life sciences, and pharmaceutical industries, we suggest and help our customers with the best ways to reduce costs and mitigate implementation risks. We work with you throughout the implementation, so that you can quickly identify, address, and record any production, shipping or quality control risks, events, and complaints. A personalized, flexible D365 dashboard equips your teams to trigger a hold on products throughout the supply chain autonomously, launch nonconformance reports, send notifications to managers when test results hit a certain threshold or when a specific research milestone deadline is compromised.

Reach out to us for your company’s Digital transformation

Get Started Now

Top concerns of biotechnology industry current issues banner
  • Xcelpros Team
  • No Comments

Top Concerns of Biotechnology Industry Current Issues
Top Concerns of Biotechnology Industry Current Issues 700 500 Xcelpros Team

At a Glance

  • The world has turned its hopes towards biotech companies to reduce the spread and impact of the Covid-19 pandemic.
  • The biotech industry is working continuously towards fortifying healthcare systems, enabling serosurveillance to gauge the spread of disease in a community and to aid in the development of a vaccine.
  • With governments across the globe funding research and production costs to enable biotech companies to win this battle against time, there are various operational, technological, and workforce concerns that these companies face that need to be addressed with strategic maneuvering from the apex.

Introduction

The Biotech and Life Sciences industry is one of the most sought after sectors this year in conjunction with the pharmaceutical industry as a solution to the current Covid-19 pandemic. Health experts across the globe have agreed that highly effective treatments, including the development of a vaccine, would be needed to reduce and eventually stop the spread of novel coronavirus, allowing cultures around the world to get back to normal activity. While some countries have fared better than others in handling the Covid-19 health crisis, there are still looming fears of new waves. Current Biotechnology issues are expected to normalize with an effective antidote or vaccine.

While the biotech industry sprung into action to begin developing a solution almost immediately, there’s still a long way to go. Challenges faced by biotechnology have been as real as the crisis itself. While the biotech and life sciences industry has a primary role in addressing pandemics like that of COVID-19, it’s not immune to economic downturns, supply chain disruptions, workforce shortage, or any other challenges.

Below are some of the pain points that the Biotech and Life Sciences industry are facing:

01.Roadblocks and Hurdles

All over the world, various biopharma companies, both privately and through government-funded efforts, are performing clinical trials for different potential vaccines and drugs. In 63 days after the genome sequence of the novel coronavirus was shared with the world, USA’s Moderna Biotech Inc. had developed its mRNA candidate to battle the pandemic. Being able to move at a pace never seen before requires immense talent, robust AI-enabled software setup to perform bioinformatics processes, and exceptional R&D infrastructure.

The journey from vaccine development to approval and administration on a global scale is wrought with numerous additional steps and hurdles, requiring mobilization of assets and task forces, recruitment of volunteers, conducting clinical trials, collation, and analysis of humongous amounts of data, smoothly operating supply chains, enormous monetary investments, and a well-equipped production and distribution infrastructure.

02.Collateral Delays

The spread of the coronavirus pandemic brought most of the world to a screeching halt, with many businesses having been forced to close. A result of this is disruptions to major clinical trials and research work on medicines and vaccines for other life-threatening diseases like cancer, HIV, autoimmune diseases, etc. These are collateral delays, and the biotech industry is now challenged with not ignoring existing health issues while still focusing on developing a solution for the ongoing pandemic.

03.Global Distribution

Health experts and top executives at significant biotech companies agree that even if we succeed in making an effective vaccine for Covid-19, there would be a need for immense strategic and operational changes in the current global and local supply chains to ensure that it’s produced and distributed to everyone around the world. With disruptions to most supply chains, only adding to challenges faced by the Biotechnology industry, it will be interesting to see how these organizations address these issues.

Figure 1Covid-19 Vaccine Development in Phases: The Role of Biotech and Pharma

Covid-19 Vaccine Development in Phases: The Role of Biotech and Pharma artwork

04.ROI

A global health crisis of this scale requires a humanitarian approach to ensuring treatment is available to all. This is why most pharmaceutical and biotech companies have agreed that the first or even second batches of any drugs or vaccines they produce(should they prove to be valid) will be distributed at non-profitable rates. We shouldn’t, however, neglect the current biotechnology issues who are investing millions of dollars in rising to the occasion. These organizations will need a blueprint for steady business growth and monetary returns in the post-COVID era.

05.Remote Solutions

Now more than ever, biotech companies need highly skilled and experienced scientists, health experts, and paramedical personnel who can make this journey towards vaccine development smooth. With most businesses still not fully operational to support new workplace requirements, more remote access solutions will have to be developed and embraced to keep operations moving forward.

Role of Microsoft Dynamics 365 Supply Chain in Biotech Companies

We have spoken about some ongoing challenges faced by the biotechnology industry in the war against Covid-19. It is important to note that current biotechnology issues are handled with strategic realignment and robust Enterprise Resource Planning tools. An ERP system such as Microsoft Dynamics 365 Supply Chain enables biotech companies of all sizes to optimize their supply chains, mitigate costs on manual labor, avoid redundant efforts, automate billing cycles, and other enterprise-level processes.

Key Takeaways

These are challenging times for organizations in the Biotech and Life Sciences industry. They now, more than any other sector, continue to work at unprecedented speeds to help the world end this global crisis. Billions of lives are at stake, waiting anxiously for a solution to the ongoing pandemic. There are many challenges that the biotech sector needs to address from disrupted supply chains to the need for multi-layered coordination for clinical trials. With strategic intervention by strong leadership and the use of modern robust tools, these challenges and more, can all be overcome.

Get Consultation For all Your Business Needs

Get Started Now

AI ml in chemical industry
  • Xcelpros Team
  • No Comments

Transforming Business with AI and ML in the Chemical Industry
Transforming Business with AI and ML in the Chemical Industry 700 500 Xcelpros Team

At a Glance

  • Innovation is the name of the game for chemical companies to optimize operations and enhance profits. To fast-track innovations, use of AI and Machine Learning in the chemical industry is crucial.
  • Many in the chemical industry are touting benefits of leveraging AI and machine learning to analyze data, systemize processes and mitigate errors by minimizing manual interventions.
  • Human-machine combination is proving to be a transformational phenomenon that can change the way the chemical industry is functioning in the USA and all over the world.

Introduction

The world is growing and seeing changes at an unprecedented rate. The year 2020 has shown us that advancement in science, especially the field of chemicals (and related fields such as biotechnology that deal with the vast majority of chemicals), cannot come fast enough! We need faster, error-free methods to test chemical molecules, computer-generated models for process optimizations, and digitally-adept sensors for quality controls. AI and machine learning play an integral role in efficiently taking the chemical industry towards a trend of modernization and innovation.

The path to digital transformation involves infusing AI into crucial processes and milestones. The journey includes digitizing assets, automating processes based on those assets (known as digitalization), and then creating new ways of doing business.

Figure 1 AI is the greatest commercial opportunity in today’s economy

AI is the greatest commercial opportunity in todays economy

When organizations invest in AI, the goal is to create and enhance digital experiences. AI apps can employ skills to mimic human cognitive functions such as vision, speech, and natural language understanding. By including these human-like capabilities, AI can enable organizations to construct digital experiences that are smart, fast, and helpful to end-users.

A recent study by Accenture shows some promising figures when it comes to use of artificial Intelligence in the chemical industry. According to research, companies that have implemented Industrial AI in the chemical sector are exhibiting significant benefits as follows:

72%report a minimum 2x improvement in some process KPIs

37%report a 5x improvement in KPIs

4 Ways of Applying AI and Machine Learning in the Chemical Industry

While every enterprise has its blueprint to follow when it comes to the application of tools and techniques on AI and Machine Learning, certain broader areas can be common for the chemical industry. Let us have a look at 4 such facets:

01.Data Crunching and Analysis for Molecular Activity Studies

Understanding chemical products and utilizing them for desired effects usually take years of analytical studies, laboratory experiments, clinical trials, farm trials, etc. However, these days, faster results that can mitigate manual errors and minimize efforts are required. Machine learning and AI tools are effectively used to feed and churn a humongous amount of data, and can systematically analyze the said data. This data churning and analysis will help separate chemicals that are effective yet have fewer or no side-effects from the ones that do not have desired effects or are toxic. Apart from the use of AI and machine learning in the pharmaceutical and pesticide industry, possibilities can also be explored in the manufacturing industry, which is heavily dependent on chemicals. Applying AI and machine learning in the chemical industry can also help expedite the efforts in fighting climate change by estimating the damage done by harmful pollutants. This will aid companies in making essential changes in their machinery and processes to minimize the pollutants being released into the water bodies and air.

02.Result-oriented Innovation and Boost in the Chemical Industry R&D Sector

R&D forms the backbone of any industry, and the chemical industry is no exception to this. Today, major players in this sector are looking for focused R&D and innovation that can yield faster and more accurate results following the use of artificial intelligence in the chemical industry. Machine learning tools can help in exercising this type of quick research with the help of computerized permutations and combinations. It can also help in recognizing the right molecules, generate formulas, and aid in knowing the precise quantities of different chemicals required. AI, on the other hand, can help in predicting chemical combinations that can be a breakthrough in terms of innovation. These innovations can boost the ongoing and upcoming efforts in the pharmaceutical, food, biotechnology, oil and gas, petrochemical, manufacturing, and many such industries.

03.Seamless Juxtaposition of Human and Machine Efforts

Since the introduction of computers in the workplace, humans and machines have proven to be the best combination for effective results. However, digital transformation and the introduction of layers and layers of machine-generated intelligence can make this combination even more successful than ever before. Imagine an idea that has come out of the human mind, but it can be analyzed, tested, and streamlined to mitigate risks or errors even before it has physically been put to the test? This can lead to unprecedented time and efforts being saved. Such amalgamation of human and machine efforts can influence the chemical industry to fast-paced innovations, productions, operations optimization, and other concurrent developments.

04.Preventative Measures and Predictive Forecasting

In today’s industrial world, competition is steep and it is essential for enterprises in the chemical industry to be prepared and to be proactive. AI and machine learning tools can help a great deal in this by predicting snafus or future maintenance requirements. Advanced analogs and mathematical models can also be used to estimate oil, gas, and other raw material demands so that the companies can streamline their supply chain in a manner that avoids potential delays and last-minute cost hikes.

While these applications of AI and machine learning cover the broad spectrum when it comes to the chemical industry, there is still a lot of research and development going on in this field. As the world embarks upon a new journey of Industry 4.0, it would be interesting to see more transformations brought in by the use of artificial intelligence in the chemical industry.

Where is the Challenge?

AI-enabled systems are helping companies achieve objectives, goals, and enhance user experience. However, each time a system is not maintained correctly, the process begins to decay by behaving unpredictably. Organizational leadership can thus lose confidence in AI as a process enhancement system. Moreover, organizations should have the required maturity—which encompasses strategy, culture, organizational structure, and core capabilities—to own an AI-based system responsibly. In some cases, this may mean a withdrawal or rejection of AI technologies based on unsuccessful attempts to adopt AI. Organizations or their customers may lose trust in AI as a technology, branding it as unpredictable or too hard to operate. This outcome will push real digital transformation further away and cause the organization to miss out on the powerful impact that AI can have on their business.

Microsoft has worked on defining an operational model that helps organizations assess their attributes that contribute to the adoption of AI technologies. A well designed AI Maturity Model assists organizations in gathering information related to the core characteristics required for teams. Forward-thinking organizations that have embraced AI are witnessing improvement in user behavior. The transformation meets all prime objectives of a Chemical company, mainly driving productivity, sales, Environment Health and Safety, appropriate management of hazardous chemicals in the warehouse.

Figure 2AI Maturity Model

AI Maturity Model

Additionally, Microsoft has compiled prescriptive guidance associated with adopting the right AI technologies for an organization’s current maturity level, while advising on how to increase maturity to embrace more advanced AI capabilities.

Key Takeaways

  • AI and machine learning in the chemical industry can be critical players in clinical trials, farm trials and overall study of chemical molecules.
  • With the cutting-edge application of AI and machine learning tools, the chemical industry can streamline its processes and supply chain for better operations and enhanced profitability.

Explore how you can transform processes, engage customers, and modernize your apps with Microsoft Business Applications.

Predictive analytics in the pharmaceutical industry key use cases banner
  • Xcelpros Team
  • No Comments

Predictive Analytics in the Pharmaceutical Industry: Key Use Cases
Predictive Analytics in the Pharmaceutical Industry: Key Use Cases 700 500 Xcelpros Team

At a Glance

  • The digital era has given companies various tools and techniques to help pharmaceutical manufacturers optimize and streamline their operations, and predictive analysis is one such highly advanced method.
  • There are different ways with which predictive analytics can integrate with existing software setup and forecast plausible technical glitches and predict future trends, thus helping in enhancing operational efficiency.
  • Predictive analysis can help planning to execution, aftermarket services level to develop better products/ services, improve their response time, and stay ahead of the curve for delivering better customer experience.

The Role of Robust Infrastructure

Database management has become one of the topmost priorities for companies across the globe. This database is used to fabricate trends and patterns for a particular time-frame or a process or a product. Data historians have been around for quite some time now, but manufacturers have recently started to look at them as more than software that stores and retrieves data. Application of predictive analytics is turning out to be a game-changer in terms of predicting the future with maximum accuracy and helping manufacturers make the right calls across various functions- purchase, operations, consumer demands, marketing, and more.

Any business operates with the ultimate motive – to enhance productivity and profits. Optimizing operations thus becomes a must for manufacturers. Companies are riding the digital wave with cutting-edge technologies and tools such as Cloud, Internet of Things (IoT), Machine Learning, and Digital Analytics. By making the most of this digital disruption and using predictive analysis to their advantage, companies can achieve better operational efficiency and higher productivity.

Increased and better predictability for both structured and unstructured data helps companies in planning their operations accordingly for enhanced productivity and a faster pace of work.

Predictive Analytics in Pharmaceutical Operations

Predictive analytics is creating a buzz in the Pharma industry for quite some time now. Different pharmaceutical manufacturing companies are looking to model their business processes by gauging the future requirements. The predictive analysis makes use of data historians to accurately make predictions about future trends, possible glitches, and diversions along the road. While technology has come a long way when it comes to predictive analysis, at an enterprise level, there are many things you can do to make the most of this technique.

93%

of healthcare executives stated that predictive analytics is important to their business’ future.

Source: CIO.com

As major companies are competing to stay ahead, product sales and consumer acceptance of a specific drug are a few contributing factors that help decide on advancing to Predictive analytics.

Here are a few ways that predictive analytics helps Pharmaceutical operations become more streamlined and agile:

01.Predictive analytics assets help in understanding patient needs ahead of time

For years Pharma companies have invested heavily in market research and insight experts to understand various geographies and patient domains. This included research to understand and forecast patient needs and medicine usage compliance to help both R&D and manufacturing teams prepare them ahead, thus catering to the requirements of the patient base. Predictive analysis plays a vital role in this domain by taking historian data and mining it to populate trends and patterns that can be used by Pharma companies to decide upon the demand for their product. Advanced digital analytics is also capable of generating models based on consumption density for a particular geography, demographic, and health index of the patient base. A pharmaceutical company, thus, would automatically be empowered by knowing its end customer base better and learn the composition of drugs and approximate quantities to produce. You can, therefore, produce the medicines as per the forecast and restructure your supply chain as per the demand. All this will optimize your operations by streamlining both the production department and your supply chain. This will result in enhanced productivity and reduced risks of stock-outs or inventory influxes.

02.Digital analytics plays an imperative role in predicting plausible manufacturing equipment glitches

Anyone working on a production line can vouch for the fact that faulty equipment can cost fortunes by becoming the reason for slowed down or altogether stopped production for days. What predictive analysis does is that it uses the stored equipment data and runs the algorithms to understand the working patterns of any equipment. This, in turn, helps in generating reports for plausible scenarios of equipment malfunction. The production team can get forewarned and can work on the said equipment beforehand to prevent any glitches. Apart from helping in enhancing the operational efficacy, this can also help in preventing loss due to stalled production.

One can take the predictive analysis a step further and use the trends generated to get into a proactive maintenance mode, rather than a more cumbersome and costlier reactive maintenance option.

9%

uptime improvement can be achieved by ensuring predictive maintenance in factories.

Source: A Report by PWC

03.Predictive analytics enhances operational efficiency by enabling risk assessment

Predicting the actions and production outcome of a batch record has become integral to measuring the performance of a Pharma product line. Predictive analytics helps in this assessment with maximum accuracy. It also helps in proactively foretelling issues risks related to product line performance, which allows Production Managers to mitigate these risks to raise product quality standards, and hence become a key driver in increasing product performance in the market. This could apply to both software and hardware in a production line. The cumulative phenomenon results in better risk assessment. This helps the operations team to proactively plan the course of their actions for a better outcome. The advanced predictive analytics tools integrate with different software used by the manufacturers to recognize patterns, share information with other machines and apply the principles of machine learning to automatically gauge risks and alert the users on a timely basis. For optimized operations, risk aversion plays an important role.

Figure 1Use Cases of Predictive Analytics in Pharma

01

Deriving 360 degree patient journey insightsDeriving 360 degree patient journey insights

02

Influencing patient adherenceInfluencing patient adherence

03

Capturing genomics data to accelerate discovery of precision medicineCapturing genomics data to accelerate discovery of precision medicine

04

Speeding up drug discovery and developmentSpeeding up drug discovery and development

05

Improving the efficiency in clinical trialsImproving the efficiency in clinical trials

06

Identifying gaps in compliance to streamline regulationsIdentifying gaps in compliance to streamline regulations

07

Reducing cost and speeding up time-to-marketReducing cost and speeding up time-to-market

08

Improving safety and risk managementImproving safety and risk management

09

Managing operations and employee trainingManaging operations and employee training

10

Taking effective sales and marketing initiativesTaking effective sales and marketing initiatives

04.Advanced analytics is essential in accelerating operations

The ways mentioned above with which advanced predictive analysis helps in operational efficiency have all resulted in more agility in the overall operations. Rapidly delivering medicines to the end customer, is becoming a primary responsibility for Pharma companies within the Pharma Value Chain. Companies see a rapid generation of patterns, demands met with more ease, lower risks in manufacturing processes – advancing production lines, and related functions to be more agile.

Business Scenario

Meridian Medical Technologies, a Pfizer company, continues to experience manufacturing challenges in the production of EpiPen® (epinephrine injection, USP) 0.3 mg and EpiPen Jr® (epinephrine injection, USP) 0.15 mg Auto-Injectors, and the authorized generic versions of these strengths. These challenges are expected to result in tighter supplies and greater variability in pharmacy-level access at this time.

Added to the shortage of EpiPens due to tighter supplies, the U.S. Food and Drug Administration provided additional information on lots that are about to expire creating further risk in Epipen availability for the patient base.

A good model of predictive analytics in the Pharma supply chain that provides a gauge of stock requirements based on patient demand, in-store inventory, and expiration dates would have mitigated this risk of Epipen outage before it is too late. Time to market is an essential factor in deciding the success of a product. Accelerating pharma manufacturing processes will thus help companies stay ahead in the competition.

Key Takeaways

  • Predictive analytics is highly effective in risk assessment, equipment analysis, trend forecasting, and data mining.
  • Every industry has their specific criterion to make use of predictive analysis to boost sales and with better use of such tools, enterprises will be better prepared to serve their customer base.
  • Manufacturers can benefit highly from this advanced digital technology by optimizing their operations and enhancing the speed of production.
  • Speeding up the medicine to the market process by predicting demand based on patient demographic enables Pharma companies to be prepared for the increase in end-customer demand and manage stock outages without compromising patient needs.

Reach out to us for your company’s Digital transformation

Get Started Now

enhance supply chain planning within pharmaceutical operations banner
  • Xcelpros Team
  • No Comments

Enhance Supply Chain Planning within Pharmaceutical operations
Enhance Supply Chain Planning within Pharmaceutical operations 700 500 Xcelpros Team

Introduction

The COVID-19 pandemic has created significant changes in market dynamics, forever changing the face of the global economy. Along with the pandemic’s impact on our daily lives, there has been a ripple effect in the day-to-day operations of Pharmaceutical manufacturing. As industries around the world continue to adjust to changes, Pharmaceutical manufacturers in specific, are noticing technology, process, and infrastructure gaps that are impeding growth and sustainability. Additionally, businesses that were forced to slowdown production during the initial stages of COVID-19 and are now getting back to full momentum, are finding it difficult to manage end-to-end operations.

Pharmaceutical companies cater to a customer base that is dependent on their products to manage patient health. This requires additional efficiency in everything they do, especially for planning supply-demand. The primary objective is to not halt manufacturing, as the dependencies can impact the entire Pharma value chain. Since pharma companies are quality controlled, there is an additional time factor that comes into the picture while determining the right deadlines to produce finished product and deliver to end customers. The entire process from drug discovery to packaging for delivery is a series of collaborations within the supply chain before the final product reaches the end customer.

Roughly 66% of the surveyed were concerned that COVID-19 could result in a possible supply chain disruption for pharmaceutical products. The statistic illustrates concern levels on possible drug supply chain disruptions due to the COVID-19 pandemic as of April 7, 2020. Matej Mikulic | Statista

The Planner’s Panorama

Due to the rapid changes in the global supply chains, production planners at pharmaceutical manufacturing are now tasked with surveying inventory and operations with a new set of eyes. Organizations need to be more watchful of new safety standards related to inventory storage, retrieval, usage of material, and equipment maintenance. Tools like Visual Gantt Charts are becoming invaluable for planning and managing inventory. The ability to depict a weekly schedule of operations for different production jobs and a clear picture of resource capacity is a core requirement for any good production planner. The production planner’s prime focus is to ensure there are enough raw materials and resources (equipment or human resources) to ensure a near-to-perfect supply-demand ratio. An additional element that supports a planner is to have inventory visibility within their current warehouse and plan transfers of inventory from overflow warehouses.

Operations gantt in batch manufacturing

Simple visual planning methods are no longer adequate to correctly manage all inventory-supply-demand processes and ensure proper movement of transactions across the company’s supply chain.

What planners need is a robust system that can track supply – demand by including a complex set of parameters such as lead times, working calendars, the capacity of equipment and capability of vendors to ship materials on a timely manner. Planners also need the ability to alert different departments of the next steps based on plans made for upcoming weeks or months. Any modern system should be able to offer required insights including the current state of batches manufactured and available equipment for future work orders.

A production planner often prefers handling the supply chain proactively rather than reactively by responding to the demands. The planner needs visibility of when the finished product will be ready, tested, and released for shipment. This type of planning helps overcome downtime and shortages in raw materials, which is a common issue in most companies. Responding quickly to changing inventory is one way for planners to be more proactive.

Process manufacturing operational efficiency

Even today, many small and medium-sized pharmaceutical companies continue to use a combination of excel sheets, inventory reports, and some old school methods when managing their supply chain. As industries continue to face changes related to the COVID-19 pandemic, only companies that have thought ahead and have invested in an automated AI-based planning system that can assess and predict future demand as well projected resource plans will be best equipped to handle their product delivery on time and in full. Companies now need a quicker and more streamlined process to take their products to market.

The Role of a Master Planning and Scheduling System

01. MPS Driven by Demand

The goal of a Master Planning and Scheduling (MPS) system is to provide suggestions to meet material requirements. If set up correctly, MPS systems respond to demand and plan supply accordingly. Demand usually comes from sales orders recorded in the Order Management system. Master planning ties Planned orders for Production or Procurement to corresponding sales orders. The supply requirements are then calculated based on settings for each item that is included in the Finished Goods Bill Of Material(BOM). The coverage settings of an item show precisely how and when to send feedback with a view of current stock levels or foreseen changes in stock levels from existing planned orders in place.

02. Planned Supply

MPS systems use algorithms for tracking the demand from sales orders, customer forecasts, safety stock levels, and calculating net-requirements for purchase and manufacturing. MPS also pulls together independent or groups of demands that trace back to the production of intermediate and raw materials to be consumed in different Manufacturing and Packout processes.

Determining the quantities required would depend on the inventory quantity setup of any single item. The requirement could be specific for a static batch size or dynamic quantities based on the demand needs. MPS systems provide planners the capability to either consolidate supplies across multiple demand orders, offering a comprehensive supply and demand management experience, or consider only the net change from the start of a full production run.

03. Lead Times

The ability to define lead times is critical to a master scheduling system. For instance, if a user enters a purchase lead time the system should account for the time it takes to receive raw materials after placing a purchase order.

I. Purchase Lead Times

Purchase lead times for a supplier can be set up based on different factors including

  • Pricing agreements
  • Time in days that a supplier can accommodate
  • Transportation time, and
  • Any other unforeseen coverage settings

Within Dynamics 365 Finance and Supply Chain, a purchase lead time found for a specific supplier and item combinations takes precedence over general settings of an item. This applies when (1) no vendor is assigned to the item, and (2) the Find trade agreements checkbox is selected via Master planning parameters form > Planned orders tab.

II. Production Lead Times

Production lead times are the details that can be configured in coverage settings; however, these values are disregarded when items are produced via routes. Routes, defined in the modern Production control modules, consider available resources (people or equipment) and their working schedule. In this situation, production lead times needed to create finished goods do not have to be specified by a user, as they are calculated automatically.

Planning for the Unknown

There are still unknowns within pharmaceutical production and operations. Without the right system, planners will struggle to retrieve the data needed to better streamline the manufacturing process. To help with this, Production Planners can benefit from valuable information like –

  • Batch production history and patterns of user behavior that show actual production lead times
  • Quality standards of work-in-process production run based on raw materials that are procured from specific suppliers
  • Quantity yields of past batches, actual scrap percentages based on changes in production routes and resources
  • Accurate actual batch costings in comparison with estimates

These additional details provide supplementary insights to help improve production, downtime planning, maintenance, and most importantly, promise dates to customers. Production planners need to be equipped with a system that presents elaborate sets of insights and actionable suggestions on how to plan/schedule production operations. A well reliable tool empowers a company to drive efficiency and growth.

An AI-ML & Analytics Centric Approach

Eventually, and soon, a standard planning system will no longer be capable for the Pharmaceutical supply chain to operate efficiently. Systems that reduce human effort, learn from history, and improve daily operations will become necessary to overcome inefficiencies. At the same time reporting possible issues and roadblocks that impact orders as well as deliveries, improves the overall plan vs actual picture. Production planners are proving to be more efficient when they have real-time and historical analytics available during the planning process to make better decisions while managing inventory and orders. A guided method of operating and reporting through actionable data can make your company a powerhouse within the industry. An intelligent and optimized planning system can help eliminate guesswork for the production planners in build a competitive edge in the market.

Final Thoughts

The supply chain within a pharmaceutical company is only as efficient as the ability of a planner to proactively coordinate supply, demand, and inventory. A robust planning system with an emphasis on analytics and guided user behavior can play a key role in building efficiency and moving shipments out the door, along with meeting the required quality standards.

Xcelpros has designed Microsoft’s offerings to enhance planning for Pharmaceutical, Chemical, or Biotech industries. For more information on Production planning and Scheduling tools within Microsoft – Schedule Demo

Data Migration – Challenges and How to resolve them
  • Xcelpros Team
  • No Comments

Data Migration – Challenges and ways to Resolve them
Data Migration – Challenges and ways to Resolve them 1550 750 Xcelpros Team
Maintaining an Integrated Supply Chain Key Solutions
  • Xcelpros Team
  • No Comments

Maintaining an Integrated Supply Chain: Key Solutions
Maintaining an Integrated Supply Chain: Key Solutions 700 500 Xcelpros Team

At a Glance

  • Many organizations that fail to recognize supply chain as a strategic business function, tend to not move to a digital supply chain and lose out on the benefits that come with the transformation.
  • Traditionally, manufacturing companies have treated supply chain as a transactional function, a bargaining chip to reduce price and secure on-time delivery of raw materials. The modern supply chain is viewed as a strategic asset to the organization, integrated deeply with other business functions, aimed to increase customer satisfaction.
  • Companies unable to track hidden costs across the supply chain lose track of actual costs, damaging their bottom line. Proper supply chain monitoring can save anywhere from 20-30% of distribution costs.

The Supply Chain Challenge

Supply chain management is one of the most critical elements of success for any business in today’s global market. However, its application is undermined by many companies as business leaders face challenges to control the cost of a supply chain without compromising on its efficiency. Since COVID-19 we have witnessed drastic changes in methods and methodologies for streamlining supply chain operations. It, however, doesn’t take away some key fundamentals required for healthy functioning of a company’s supply chain and inventory management.

According to the Logistics Bureau, for companies running global operations, their supply chain cost could rise as high as 90% of their total expenditure.

The Supply Chain Slowdown

The problem lies in poor strategic management. Supply chain managers are focusing on cost minimization, most of them without having detailed field knowledge of how the system works, and the result is it is impacting other areas of the process such as inventory optimization, ‘on-time delivery in full (OTDIF)’ and customer satisfaction. Trying to improve one KPI is resulting in a cost spike in other areas of operations, which can have a long-term impact on revenue.

FIGURE 1 Where Business Leaders are Falling Short

Where Business Leaders are Falling Short

A robust supply chain needs strategic alignment and planning in line with the overall business functioning. For example, in order to control cost, you need to first understand the key drivers of cost in the supply chain and most importantly how to measure the supply chain cost. While the strategy is important, establishing an integrated supply chain requires a synchronized approach to planning, execution, and application of technologies in order to create an end-to-end unified system across the entire organization.

FIGURE 2 Key Elements of an Integrated Supply Chain

Key Elements of an Integrated Supply Chain

In this article, we will touch upon some interesting facts that make an appealing case as to why the Supply Chain strategy needs to be digitally enhanced and properly integrated with other parts of the business.

Switching from Traditional to Next-Gen Digital Supply Chain

The rapidly evolving business landscape is disrupting the way companies function. Moreover, the advent of the latest technologies and growing competitive markets are driving companies to push their limits and redefine supply chain operations.

Is your business ready to embrace a digital supply chain as a key distinguishing factor for its competitive advantage?

Most SMBs are holding back the transformation due to the fear of possible risks that could surface. Per our industry experience, it’s due to the age-old perspective in which company leadership is analyzing their supply chain. In most of the cases, we found that they are way behind the entire purview and don’t realize the true potential of a well-integrated, technologically advanced supply chain.

Traditionally, business leaders focused on pricing and product quality, but priorities today have completely shifted. Major Objectives and Key results of organizations are geared towards optimized supply chain and operations to boost businesses forward. With Industry 4.0, advanced analytics, and robotic process automation rising, companies are realizing the need for an integrated supply chain. This has become even more true as the Covid-19 crisis continues. Demand planning and fulfillment, supplier-customer relationship, customer retention, on-time delivery are some of the major expenses of a company. An efficient supply chain not only helps with cost reduction in these segments but also ensures growth, profitability, and customer satisfaction.

Top Reasons to Upgrade Your Operations with a Next-Gen Digital Supply Chain:

Shifting from a plant-level production planning to a demand-driven focus with customer-centric mindset but not compromising with the product quality

Getting rid of outdated processes and technology to match the transforming global business landscape

Reducing cost to formulate a more efficient value chain to remain cost-competitive in the market

Ability to outsource parts of your supply chain process in order to reap economic benefits and superior supply chain network design

Achieving more efficient product lifecycle management

Collaboration with stakeholders to integrate business processes for increasing visibility throughout the value chain

The Impact of Supply Chains

An integrated supply chain influences the overall functioning and improves profitability of the business. Going digital and increasing interoperability across these functions sets a business up to accelerated growth. Let us discuss a couple of key areas that are impacted by a well designed supply chain.

FIGURE 3 Upgrading the supply chain will improve your bottom line

Upgrading the supply chain will improve your bottom line

01. Supply Chain and its Impact on Customer-Centricity

When business leaders discuss improving their supply chain, their main focus is usually related to accelerating growth by cutting down costs, achieving better lead time, and ensuring on-time delivery; as all these factors contribute towards business development. What slips from their mind is what customers really care about. It all starts and ends with customer satisfaction. Delivering the right product at the right time improves your organization’s brand value and credibility to customers.

What the customer cares about is receiving quality products on the promised delivery date without having to spend too much time or effort. This can be seen in Amazon’s announcement of one-day delivery. Late and inaccurate deliveries bear a significant impact on customer loyalty.

70%

of industry professionals predict that their supply chain is going to be a key driver of improved customer satisfaction by the end of the year.

Source: Accenture

Your procurement division must understand the importance of cost-saving, but they need to be in line with the expectations of the customers and procure quality raw material for manufacturing the items. If expectations on raw material quality is not set, you could save money purchasing raw materials upfront, but end up spending more in the long run.

Let’s take a look at Kimberly-Clark’s journey to understand this better:

Kimberly-Clark is a manufacturing-focused organization that up to a few years ago did not have a supply chain division. Sandra MacQuillan, their first Supply Chain Officer, built a solid team to ensure the supply chain was focused on customer satisfaction. In the process, she integrated various functions such as procurement, quality (know more on quality management by clicking here), logistics, manufacturing, safety, etc. that are interconnected and delivered for one common goal – that is customer satisfaction.

Kimberly-Clark was able to achieve 25-30% cost savings by interconnecting various aspects of the Supply Chain, focused on better customer service, resulting in improved efficiency.

If you connect with the issues faced by Kimberly-Clark, or your supply chain is functioning in silos, it could be the best time to make a change. You can take this opportunity to update and integrate your supply chain with overall business functions and work towards a common goal like customer Satisfaction. A strongly integrated application will have the ability to incorporate holistic business functions including analytics, collaboration with notification, secure information sharing, control-based decision making using Artificial Intelligence, and more.

FIGURE 4 KPIs that are critical for supply chain monitoring

KPIs that are critical for supply chain monitoring

02. The Role of supply chain in sustaining business long term

According to the Logistics Bureau, nearly 50% of companies shut down within the first five years of operation. One critical factor contributing to these failures is an inefficient and poorly conceived supply chain. Supply chains in most organizations have evolved as a practice, rather than a well-designed process.

79%

of companies with robust and high-performing supply chains are able to outperform their average peers in terms of higher revenue growth. This fact signifies the positive implication of a connected supply chain for a business.

Source: Deloitte

5 Steps to Integrate your Supply Chain

Break down organizational silos

For an effective, integrated approach to Supply Chain Management (SCM) the organization must operate end-to-end as a unified entity.

01

Define organizational objectives

Move beyond basic business and functional unit design and metrics. Look at the organization holistically and define the objectives as a complete entity.

02

Align business processes

Take a cross-functional approach to business process design. Start at a high level and map out the supply-chain flow with the goal of creating an end-to-end mapping of the business process.

03

Design the IT architecture to support an integrated approach

Leverage a cross-functional approach to IT systems design. As much as possible, standardize the organization in terms of the applications that are used. Seek to eliminate as many disparate applications as possible in favor of a common set of applications across the business.

04

Reshape leadership and culture

For most organizations, the major roadblock in delivering an integrated approach to supply-chain management is culture change. Change of this magnitude must be driven by solid leadership. There should be strong collaboration to drive the effort to deliver an integrated supply-chain organization.

05

Final Thoughts

There is no way the importance of an integrated Supply Chain should be overstated or undermined. If you or your organization have not prioritized your supply chain efforts, it’s never too late to take the first step.

An intelligent ERP software comes with a holistic supply chain module along with advanced analytics to support the following functionality.

  • A manufacturing execution system
  • Financial and cost accounting
  • Inventory and warehouse management
  • Purchasing and planning of materials
  • Product information management
  • Sales and marketing of the products
  • Transportation and logistics management

In order to push a company forward especially post-COVID-19, a sound digital supply chain strategy would be needed.

Do not let operational inefficiencies limit your business, long-term goals

Act Now

Thinking
Unlimited!

There is no box! We believe in the limitless possibilities of human potential powered by technology.

Subscribe Now

Chicago

1 Mid America Plaza, 3rd Floor Suite #226, Oakbrook Terrace, IL 60181

Phone: 630-869-0901

Bangalore

V4 Complex 2nd Floor, Krishna Kamala Enclave, Uttarahalli Hobli, Bangalore, Karnataka 560061

Search Services, Industries, Insights, and Products