top of page

2024 - What To Watch For


Top 7 Biotechnology Trends to Watch in 2024


This article takes a look at the top biotechnology trends in 2024, tackling global challenges such as disease and emissions. It explores personalized treatments, AI-driven genetics, and innovative software that will shape healthcare and research.

Biotech’s revolutionary medical projects will revolutionize our future as we address global issues such as disease, emissions, and food management.


Understanding these biotech trends can help companies capitalize on the industry’s exponential growth opportunities.


This article explores the top seven trends that will reshape the biotech landscape:

  1. Personalized Medicine. Tailoring treatments to individuals using genetic knowledge.

  2. Gene Editing and CRISPR Diagnostics. Harnessing CRISPR and AI for precision genetics.

  3. Machine Learning and AI. Powering biotech breakthroughs with intelligent algorithms.

  4. Stem Cell Technology. Pioneering regenerative medicine with simulation and modeling tools.

  5. Tissue Engineering and Bioprinting. Creating functional organs and tissues through bioprinting software.

  6. Big Data. Revolutionizing research through advanced data analytics and management.

  7. Drug Research. Accelerating drug discovery with cutting-edge software solutions.

Throughout these trends, custom healthcare software development emerges as the driving force, turning innovative concepts into tangible biotech advances.

Embark on a journey through the biotech landscape of 2023 as we delve into these seven transformative trends. Discover how they will reshape healthcare, genetics, and research, and unlock new frontiers in biotechnology.


What is Biotech?

A branch of technology known as “biotech” uses biomolecular and cellular processes to produce goods for the food, medicine, and energy industries.

Biotech has become one of the most innovative industries, with scientific and technical breakthroughs.

According to Vision Research Reports, the global biotech market is expected to exceed $3.44 trillion in 2030, driven by the rapid growth and acceptance of emerging technologies, goods, and services that address significant problems and opportunities.

There are three main fields of biotechnology:

  • Medicine. Pharmaceuticals, treatments, genetics, and clinical trials are examples of areas where biotechnology is being used to improve human health.

  • Industry. The energy and manufacturing industries are using biotech to create small solutions using yeast, enzymes, and microorganisms.

  • Agriculture. Biotech in agriculture leverages existing organisms to modify and improve agricultural products, making them safer and more efficient to produce.

The following section will mostly focus on biotech in the healthcare industry.


Biotech in Medicine

Medical biotech is a field of healthcare that studies and produces pharmacological and diagnostic products using living cells and cell components. These products help treat and prevent disease. Medical biotech is making significant advances and helping millions of people.


Recent applications of biological technology include genetic testing, medication therapies, and artificial tissue growth.

Biotechnology in medicine has the potential to:

  • Reduce the prevalence of infectious diseases.

  • Reduce the likelihood of individuals around the world developing life-threatening diseases.

  • Create personalized therapies to reduce health risks.


Top 7 Trends in Biotech


Personalized Medicine

Personalized medicine is the practice of tailoring healthcare to individual patients based on genetics, habits, and external factors. By providing the right therapy at the right time for a specific individual, this strategy aims to improve the safety, efficiency, and affordability of healthcare.


In biotech, this is enabling faster and less expensive sequencing of human DNA to help doctors and researchers understand how genes impact health and disease, and how they respond to medications and other therapies. Among the many benefits of personalized medicine is the ability to identify which individuals are more likely to respond to certain cancer therapies or are at risk of adverse drug reactions.


According to Allied Market Research, the global personalized medicine market size was $300 billion in 2021 and is expected to reach $869.5 billion by 2031, representing a CAGR of 11.2% from 2022 to 2031.


Gene Editing and CRISPR Diagnostics

Biotech is not only improving therapies, it is also speeding up diagnostic results. The gene-editing technology CRISPR can now run many tests faster and cheaper. One way in which CRISPR technology is reducing the cost of diagnostics is by enabling patients to carry out tests at home.


Gene editing, which includes CRISPR technology, is a rapidly developing field in biotechnology, particularly for the treatment of genetic abnormalities and chronic diseases. Gene editing can be used to add, replace, or neutralize specific genes.


In addition, precision medicine is now possible through gene editing and sequencing. This allows doctors to determine the best course of action for a particular patient. For some diseases, such as various types of cancer, precision medicine also allows doctors to customize therapies.


Precision medicine is also being used by biotech entrepreneurs for drug discovery, gene therapy research, and other drug delivery methods.


Machine Learning and AI


Artificial intelligence (AI) and machine learning (ML) are areas of computer science that allow machines to perform activities that would normally require human intellect, such as knowledge acquisition, deductive reasoning, and problem solving.


Artificial intelligence (AI) continues to find applications in a wide range of sectors, particularly biotech. According to StartUs Insights, AI will be the most important biotech topic in 2024.

AI has been used by biotech companies to improve the automation of various operations. For example, AI can find biomarkers for use in drug development and diagnostics. AI algorithms can also identify human disease characteristics such as cancer cells by categorizing images.


Given the sector’s upward trajectory, we can expect to see more biotechnology companies adapting these technologies to drive innovation, particularly in genomics and drug development.


Stem Cell Technology


Undifferentiated cells called stem cells can repair damaged organs and tissues, making them an important component of regenerative medicine. Other potential uses for stem cell technologies include drug testing, disease simulation, and treatment of diseases such as Parkinson’s and Alzheimer’s.


The global market for stem cell technologies and therapies is projected to grow at a CAGR of 9.74% from 2023 to 2030. As a result, future research in these areas is expected to increase.


Tissue Engineering and Bioprinting


Bioinks made from biomaterials are used in bioprinting. Biotechnology companies use cells as substrates that expand within a scaffold to allow the patient’s own cells to form bone, skin, or vascular grafts.


Tissue engineering is a related field that has grown rapidly in recent years as a result of developments in bioprinting. Tissue engineering can be used to produce tissue grafts from a person’s own body to heal burns. These tissue grafts can also be used in regenerative medicine and organ transplantation.


For example, 3D Biotechnology Solutions is a Brazilian company that develops bioprinting solutions. The company’s 3D bioprinter, Genesis, is aimed at tissue engineering and regenerative medicine researchers.


Big Data


The amount of data available for biotech analysis has never been greater. With the integration of sensors and the IoT, biotech scientists now have unprecedented access to data.


The management and preservation of EHRs is an issue that the healthcare industry and big data are now addressing. The US government is investing $19 billion to accelerate the use of electronic medical records.


With medical records stored in a directory, the medical field has a pool of data to work with to improve diagnosis and treatment.


For example, BioXplor, a German company, is using big data to develop better and safer treatment regimens. It uses network pharmacology to create treatments from disorganized and disparate data sources. The startup’s approach detects whether drug combinations have synergistic or antagonistic effects. It also mines patient information for responder and non-responder signals to improve patient results and analyze treatment response.


Drug Research


Advances in smart technology have made drug development one of the most promising areas of biotech. Drug development has always been plagued by problems such as finding enough volunteers for trials and lengthy production schedules that can take years. The use of machine learning has enormous potential for drug research, and also offers techniques for improving and analyzing medicine, diagnosis, and therapy.


Biotechnology shortens drug development timelines without requiring drug companies to recruit thousands of patients for clinical trials.


MRI scans, along with other in-patient monitoring tools, provide medical professionals with more objective data, allowing them to develop better pharmacological therapies for patients. As advances in biotechnology have made clinical trials less of a manual process, pharmaceutical companies can save money by enrolling fewer in-person patients in trials.

Biotech companies can use the digitalization of clinical trials to integrate genetic and biometric data to discover the underlying causes of illnesses such as heart disease.


Custom Healthcare Software Development to Bring Biotech Trends to Life


Medical software development companies can play a pivotal role in promoting and implementing the latest trends in biotech for the healthcare industry. Here’s how they can contribute to each of these trends:


Personalized Medicine


Data Integration Platforms: Custom healthcare software development companies can develop platforms that can integrate and analyze patient data from various sources, including genomic, clinical, and lifestyle data. These platforms should enable healthcare providers to tailor treatment plans for individual patients based on their unique profiles.


Clinical Decision Support Systems: A custom medical software development company can build AI-driven clinical decision support systems that provide real-time treatment recommendations to healthcare professionals. These systems can take into account patient-specific data and the latest medical research to provide the most personalized care.


Gene Editing


CRISPR Tools: A healthcare development company that is developing software tools to help researchers design and simulate CRISPR-Cas9 experiments. These tools should provide insight into target selection and help minimize off-target effects, thereby improving the precision of gene editing.


Data Analysis and Visualization: Medical development companies can develop software to analyze and visualize the results of gene editing experiments, making it easier for researchers to interpret and share their findings.


Machine Learning and AI


Disease Prediction Models: Software development companies can build machine learning models that analyze patient data to predict disease risk and progression. These models can be integrated into healthcare systems to support early diagnosis and intervention.


Drug Discovery Platforms: These companies can develop AI-driven drug discovery platforms that analyze vast amounts of data to quickly identify potential drug candidates. These platforms can significantly accelerate the drug development process.


Stem Cell Technology


Simulation and Modeling Tools: A custom healthcare software development company can create software to simulate and model the behavior, differentiation, and interactions of stem cells within the body. These tools can help researchers understand and optimize stem cell therapies.


Patient-Specific Protocols: A software development company can develop software that generates patient-specific stem cell treatment protocols, taking into account individual health records and genetic information.


Tissue Engineering and Bioprinting

Bioprinting Software: These companies can develop software to precisely control 3D bioprinters. This software should enable precise deposition of biomaterials and cells to create functional tissues and organs.


Virtual Tissue Design: Software development companies can develop tools to virtually design complex tissue and organ structures, optimize scaffold materials, and simulate the entire bioprinting process.


Big Data


Data Management and Analytics Platforms: Healthcare development companies can create robust data management and analytics platforms tailored to the healthcare and biotech sectors. These platforms should facilitate the storage, processing, and analysis of large amounts of biological and clinical data.


Data Visualization Solutions: These companies can develop data visualization tools that enable researchers and healthcare professionals to easily explore and interpret complex datasets. Interactive visualizations can help identify patterns and insights.


Drug Research


Cheminformatics Software: A software development company can create chemoinformatic software that helps analyze chemical structures, predict drug interactions, and design molecules with desired properties.


Clinical Trial Management Systems (CTMS): Healthcare software development agencies can developCTMS to streamline the management of drug development processes. These systems should handle everything from preclinical research to regulatory compliance and clinical trial tracking.


Final Thoughts


The biotechnology sector is a dynamic, fast-moving market with enormous scope for innovation and expansion. With this in mind, biotechnology companies that keep abreast of the latest trends and developments have a greater chance of success and help create a brighter future.


Advances in biotechnology are critical to transforming healthcare worldwide. As the COVID-19 pandemic showed, rapid action is more important than ever in the fight against disease.


Sigma Software collaborates closely with biotech and healthcare organizations to create customized solutions that meet specific needs and regulatory requirements. By providing expertise in custom healthcare software development, the company is helping accelerate the implementation of cutting-edge biotech trends in the healthcare industry, ultimately improving patient care and outcomes.


If you are in the biotech industry or have a biotech-related project and require healthcare software development services, please contact our Healthcare IT Solutions division for a consultation.

Ref: https://sigma.software/about/media/top-7-biotechnology-trends-to-watch-in-2024



New: 6 essential pharmaceutical industry statistics to know in 2024

What major trends and market forces point the way to pharma’s future?



The global pharmaceutical industry is facing a bold new AI-powered era (or at least it seems). While it’s true there’s a growing appetite for advanced technologies to streamline processes across the organization, life science companies are modernizing everything from clinical R&D to commercial product launches. Powerful big pharma is partnering with agile biotechs to introduce exciting new treatments. And there’s a strong focus on the patient voice, emphasizing putting choices into the hands of consumers. With so many forces at work, what are the essential pharmaceutical industry statistics you need to know in 2024? In this article:

  • Overall pharmacy spend to top $1 trillion

  • Clinical trial enrollment challenges

  • Why patients discontinue trials

  • Patient diversity in clinical trials

  • Pharma investment in artificial intelligence

  • Digital transformation and AI in pharma

Let’s dive into the year’s essential pharmaceutical industry stats.

Top pharmaceutical industry statistics

Ultimately, these numbers tell a story about the future of the pharmaceutical market. Leaders can see how the life science vertical is changing in response to everything from climate change and COVID-19 to supply chain issues and artificial intelligence. They are responding by taking steps to evolve and modernize. Here are the most remarkable pharmaceutical industry statistics:

  1. Overall pharma spend to exceed $1 trillion by 2030

  2. On average, it takes 19 months to enroll patients in trials

  3. 30% of patients discontinue trials due to a poor non-clinical experience

  4. 61% of surveyed pharma companies have defined goals and objectives to enhance clinical trial diversity

  5. AI in drug discovery could reduce drug development timelines by two years

  6. 53% of pharma finance leaders say they’ll accelerate digital transformation


#1 – Overall pharmacy spend to top one trillion by 2030

The nature of drugs hitting the market is changing. Personalized medicine, targeted therapy, digital therapies, and other specialty treatments are increasing in approvals relative to more traditional treatments – significantly impacting the cost curve.

“Over the next decade, pharmacy is ripe to change significantly…by 2030, overall pharmacy spend will exceed $1 trillion.”

The effect of more individualized and specialty drug approvals has triggered a phenomenon called “pyramid math,” where three percent of patients drive 70% of pharmacy spend. While these speciality drugs hold a great deal of promise for patients with rare diseases, they also introduce a new type of economics into the industry, in which fewer patients are essentially funding the next generation of the pharma R&D process.

#2 – On average, it takes 19 months to enroll patients in trials

Clinical trial timelines are designed to ensure that new treatments are safe and effective for patients. Therefore, it’s impossible – and not desirable – to rush them. But trial sponsors want to be efficient during the recruitment and enrollment periods, which are essential for keeping trials on track.

Approximately 85% of trials don’t begin on time due to enrollment issues. To some extent, this is dependent on the type of trial. For example, enrolling healthy participants in a trial may only take a few months. For other disease areas – rare diseases, oncology, and gastrointestinal conditions – enrollment can take years, significantly affecting trial success.


#3 – 30% of patients discontinue trials due to a poor non-clinical experience

Trial retention is an important element of successful trial execution. Study sponsors can suffer severe setbacks if enrollees don’t complete a trial. According to Accenture, the statistics are sobering:

  • Across more than 300,000 clinical trials, only 5-10% of eligible patients are even aware of the studies

  • 30% of patients drop out due to non-clinical issues

  • 19% of trials close or terminate early because they don’t have enough participants, causing an estimated $800 billion loss in value

What are the non-clinical issues that cause patients to discontinue trial participation? It’s important to remember that patients are regular people dealing with work, family, and possibly health issues, which may interfere with prescribed trial activities. Patients may find it difficult to travel to trial sites due to scheduling or the cost of transit. They also may be concerned about missing work or arranging childcare.

To minimize these issues for participants, trial sponsors investigate the benefits of decentralized clinical trials, including fewer barriers to participation and increased participant diversity. Many aspects of clinical trials – such as documentation and data collection – are already digitized. As more consumers prefer to manage their healthcare using online portals and apps, the demand for virtual or decentralized trials will likely increase.

#4 – 61% of surveyed pharma companies have defined goals and objectives to enhance clinical trial diversity

When the FDA approves prescription drugs, consumers may assume clinical trials accurately represent the population they are designed to treat. However, most trials primarily enroll white male patients – while people of color make up about 39% of the population, these groups only represent between 2-16% of patients in trials.

Clinical trials primarily enroll white male patients, with consistent underrepresentation of women, the elderly, and people of color – especially Black and Hispanic patients. While people of color comprise about 39% of the US population, these groups represent 2% to 16% of trial patients. This disparity hurts patient outcomes and drug companies’ bottom lines.

Accordingly, more than half of pharma companies have identified a strategy to address this issue. Some elements of these strategies include:

  • Working with patient groups, community organizations, CROs, and other groups to establish a more sustainable trial infrastructure

  • Updated data collection to support the accumulation and sharing of demographic and real-world data

  • Developing patient-focused resources that make it easier to learn about, enroll, and participate in clinical trials

#5 – AI in drug discovery could reduce drug development timelines by two years

Artificial intelligence in drug development offers intriguing possibilities for pharma. By finding efficiencies in the drug development process, the industry could save tens of millions yearly, bring treatments to market more quickly, and ultimately improve patient outcomes. Accordingly, the industry is increasingly relying on AI to support drug discovery. One of the most striking pharmaceutical industry statistics is that spending on AI will reach $3 billion by 2025 as companies invest in technology that may reduce the time and costs required to bring a new drug to market. AI-based drug discovery alliances are also increasing, from just 10 in 2015 to 105 in 2021.

The aim is to overcome a very low success rate in drug discovery, with just 10% of candidates making it into clinical development despite applying new computational technology techniques to handle an ever-growing amount of biomedical data. It takes 12 to 18 years and about $2.6 billion for a new drug to reach the market – even for high performers among the top 10 pharmaceutical companies.

Drug companies are also betting big on AI in clinical trials. Amgen expects AI to “shave two years off the decade or more it typically takes to develop a drug.”

#6 – 53% of pharma finance leaders will accelerate digital investment with analytics, AI

Last year, pharma leaders said they expected pandemic-related investments in digital transformation to continue. Looking ahead, more than half of pharma finance chiefs say they’ll accelerate digital transformation with advanced data analytics, AI, and other solutions to “drive standardization and automate as many processes in every area where it makes sense,” according to PwC research.

Although many life science companies have embarked on digital transformation initiatives, industry leaders must tune into the value these efforts deliver and whether their operations are truly transformed. PwC recommends using metrics to measure how many hours of work are being eliminated across a specific time frame, how much outcomes can be accelerated, and how much quality improvement they can achieve under a transformed digital framework. Pharmaceutical industry statistics: main takeaways

The pharmaceutical industry is rapidly evolving to meet formidable challenges. The strategic deployment of technology – including artificial intelligence, insights management, advanced analytics, and other tools – will support pharma teams as they embrace changing times. Organizations should also continue to emphasize developing and evangelizing patient services, trial diversity, and an overall patient-centric approach.

This year’s top pharmaceutical industry statistics paint a clear picture. While drug companies will see the benefits of digital transformation in total pharmaceutical sales, the most important benefit is to patients who will receive better drugs and treatments within shorter timelines.


Ref: https://within3.com/blog/pharmaceutical-industry-statistics

36 views

Comments


bottom of page