Category Archives: IT
Critical Areas to consider for Getting AI right
Some learnings and reflections from the Datacenter forum – Several critical areas were highlighted for getting AI right. The importance of data governance was emphasized, ensuring that AI systems are built on high-quality, well-managed data. This includes implementing robust data privacy and security measures to protect sensitive information.
Ethical AI practices were also a key focus, stressing the importance of transparency, fairness, and accountability in AI development and deployment. Ensuring that AI systems are free from biases and operate in a fair and just manner was a significant point of discussion.
Scalability and infrastructure were identified as crucial areas, with discussions on the necessity of having scalable and efficient infrastructure to support AI workloads. This includes the use of advanced computing resources and energy-efficient technologies.
Collaboration and knowledge sharing were highlighted as essential for driving innovation and addressing the challenges associated with AI. Encouraging collaboration between different stakeholders, including academia, industry, and government, was seen as vital.
Lastly, the need for continuous learning and adaptation was stressed. AI technologies are rapidly evolving, and it is crucial to stay updated with the latest advancements and continuously adapt AI strategies to remain competitive and effective.
These insights provided valuable guidance on the critical areas that need to be addressed to ensure the successful implementation and utilization of AI technologies.
https://www.datacenter-forum.com/events/stockholm/2024
Generative AI Swedish Industry cluster – Billion SEK investment to speed up the digitization of Swedish industry
Exciting news – A billion SEK investment is being launched within the research and innovation programme Advanced digitalisation which will accelerate the pace and strengthen Sweden’s position in innovation and industrial development.
Read more here: https://www.vinnova.se/en/news/2024/10/billion-dollar-investment-to-speed-up-the-digitization-of-swedish-industry/
Reach out to learn more!
Guest lecture at Lund University – the transformative role of AI and machine learning in drug discovery
The guest lecture at Lund University focused on the transformative role of AI and machine learning in drug discovery, with a particular emphasis on the AlphaFold model. The lecture began by discussing the importance of AI and machine learning in the drug discovery and development process, highlighting how these technologies are revolutionizing the field by enabling more efficient and accurate predictions of molecular structures and interactions.
AlphaFold, an advanced AI model developed by DeepMind. The model’s capabilities were demonstrated, showing how AlphaFold has dramatically improved the accuracy of protein structure predictions, which is crucial for understanding biological processes and developing new drugs. The impact of AlphaFold on accelerating drug discovery was emphasized, as it provides high-quality structural data that can be used to identify potential drug targets and design effective therapies.
The broader implications of AI and machine learning in the pharmaceutical industry were also discussed, including their potential to reduce the time and cost associated with drug development. Examples of successful AI-driven projects were shared, encouraging students to explore the possibilities of these technologies in their future careers.
Overall, the lecture provided valuable insights into the cutting-edge applications of AI and machine learning in drug discovery, inspiring the next generation of researchers and professionals in the field.
Quantum computing – what’s coming…
How we address and discuss quantum computing covers a range of important topics, reflecting the current state and future potential of this transformative technology.
One of the primary topics is the progress in developing quantum-resistant public-key cryptographic standards. Emphasizing the importance of migrating to post-quantum algorithms to ensure data security in the face of advancing quantum capabilities. Delving into the disruptive potential of quantum computing across various industries, with a particular focus on its applications in the pharmaceutical sector.
Another key area is the need for building internal expertise to differentiate between hype and genuine progress in quantum computing. Sharing learnings from working with this nascent technology is crucial for fostering a deeper understanding and practical application. Underscoring the significance of collaboration between academia, industry, and government to drive innovation and addressing the challenges associated with quantum computing.
A GREAT Pitch 2024
GREAT vill korsbefrukta all den kunskap som redan finns bland GREAT:s medlemmar och den relativt unga health tech industrin
Event information
För tredje året i rad genomför GREAT ett pitch event med startups som placerat sig i toppen bland de företag som ansökt om utmärkelsen Health Tech Award.
Compute clusters and energy consumption in a regulated environment
The topic “Compute clusters and energy consumption in a regulated environment” focuses on the implementation and management of high-performance computing systems, specifically those utilizing GPUs, to support advanced AI workloads. These systems are particularly relevant in regulated environments such as life sciences, and here addressed in settings where energy consumption and sustainability are critical concerns.
Compute clusters are composed of multiple nodes, each equipped with powerful GPUs, designed to deliver exceptional computational performance. The architecture of a compute cluster includes scalable units that can be configured to meet the specific needs of different applications. Each unit consists of several GPU systems, interconnected to ensure high-speed data transfer and efficient resource utilization.
One of the key challenges in deploying compute clusters in regulated environments is managing energy consumption. These systems require significant power to operate, and their energy efficiency is a critical factor in their overall sustainability. The design of compute clusters includes features such as direct liquid cooling and the use of renewable energy sources to minimize their environmental impact. Additionally, the reuse of waste heat generated by these systems for residential heating or energy storage further enhances their sustainability.
In a regulated environment, it is essential to ensure that the deployment and operation of compute clusters comply with relevant regulations and standards. This includes adhering to guidelines on energy efficiency, data security, and environmental impact. The governance and control over the assets, as well as the delegation of authority and budget management, are crucial aspects of managing compute clusters in such settings.
Overall, the implementation of compute clusters in regulated environments requires careful planning and consideration of energy consumption, sustainability, and compliance with regulatory standards. By leveraging advanced technologies and innovative solutions, organizations can harness the power of compute clusters while minimizing their environmental footprint and ensuring regulatory compliance.
DIPS 1000+ Inno Wave, Korea
Presenting at the DIPS 1000+ Inno Wave in Korea. Contributing to the open innovation and collaboration efforts between companies and start-ups.Key points highlighted:
The commitment to open innovation offering access to scientific expertise and world-class infrastructure. Emphasizing the importance of collaboration in driving innovation and addressing the specific needs of the life sciences sector.
Outlining various collaboration types, including joint R&D, adopting solutions, M&A, acquisition of new technology, new product development, talent acquisition, and investments. Discussing the desired technology and collaboration tasks, focusing on areas such as Bio Health, AI and Big Data, and Quantum Technology.
Engaging in discussions with potential partners, exploring opportunities for collaboration and innovation.
Data centers of the future – LLMs for everyone
Data centers of the future – LLMs for everyone – focusing on the advancements and future prospects of data centers, in the context of supporting large language models (LLMs) and making them accessible to a broader audience. The topic explores how data centers are evolving to handle the increasing computational demands of LLMs, which are essential for various AI applications, especially in life sciences.
Key aspects of this topic include:
Infrastructure Enhancements: The need for robust and scalable infrastructure to support the training and deployment of LLMs. This involves advancements in hardware, such as GPUs and TPUs, as well as improvements in data storage and networking capabilities.
Energy Efficiency: Addressing the energy consumption challenges associated with running large-scale data centers. This includes exploring sustainable energy sources and optimizing energy usage to reduce the environmental impact.
Accessibility and Democratization: Making LLMs accessible to a wider range of users and organizations. This involves developing user-friendly interfaces, providing cloud-based solutions, and offering affordable access to powerful AI tools.
Security and Privacy: Ensuring the security and privacy of data processed by LLMs. This includes implementing robust data protection measures and adhering to regulatory requirements to safeguard sensitive information.
Innovation and Collaboration: Encouraging collaboration between industry, academia, and government to drive innovation in data center technologies and AI applications. This involves sharing best practices, conducting joint research, and fostering an ecosystem of innovation.
Overall, the topic highlights the importance of evolving data centers to meet the growing demands of AI technologies and making these advancements accessible to everyone.
Into the Future: Artificial Intelligence in Business Development
Artificial Intelligence in Business Development aiming at empowering business development with generative AI tools.
Prompt Engineering: The importance of prompt engineering in achieving effective results with tools like Copilot.
Confidentiality Assurance: Concerns around confidentiality using AI for sensitive business development tasks. Data governance and the capability to respect privacy settings, ensuring that sensitive information remains secure.
Training and Adoption: The need for developing training programs for business development on effective Generative AI tooling usage.
Overall, leveraging AI technologies to enhance business development efforts, provides valuable insights and practical strategies for integrating AI tools into business processes.
Quantum Computing in Life Sciences
Quantum computing is an emerging technology that promises to revolutionize various industries by solving complex problems that are currently beyond the reach of classical computers. The initiative “Quantum Computing – the future is here, how do we use it?!” explores how we can harness this powerful technology for practical applications.
Quantum computing operates on the principles of quantum mechanics, using quantum bits or qubits, which can represent both 0 and 1 simultaneously through a phenomenon known as superposition. This allows quantum computers to process a vast number of possibilities at once, making them exceptionally powerful for certain types of computations.
One of the key areas where quantum computing is expected to have a significant impact is in drug discovery and development. By simulating molecular interactions at a quantum level, researchers can identify potential drug candidates more quickly and accurately than with classical methods. This could lead to faster development of new medications and treatments.
Another promising application is in materials science. Quantum computers can model the properties of new materials at an atomic level, enabling the design of materials with specific characteristics for use in various industries, from electronics to renewable energy.
Quantum computing also holds potential for optimizing complex systems, such as supply chains and financial portfolios. By analyzing vast amounts of data and exploring numerous scenarios simultaneously, quantum algorithms can identify optimal solutions that would be infeasible for classical computers to compute.
Despite its potential, there are still significant challenges to overcome before quantum computing can be widely adopted. These include developing stable and scalable qubit systems, error correction methods, and practical quantum algorithms. However, ongoing research and investment in this field are rapidly advancing our understanding and capabilities.
In summary, quantum computing is poised to transform various sectors by providing unprecedented computational power. As we continue to develop and refine this technology, it will be crucial to explore and implement practical applications that can harness its full potential for innovation and growth.
If you have any specific questions or need more details on any of these points, feel free to reach out!
COO Digital Strategy Visioning
A COO Digital Strategy Visioning, a significant aim at developing a comprehensive digital strategy. Bringing together key stakeholders exploring new opportunities and technologies that could enhance operational efficiency and service delivery.
Sharing of successful case studies and a working model to guide the discussions. Participants engaging in brainstorming sessions, focusing on digital opportunities such as advanced analytics, cloud platforms, and AI-driven solutions. Collaborative exercises allowing attendees to tackle specific challenges and generate innovative ideas.
Successfully capturing a wealth of ideas and feedback, analyzed and summarized for further refinement. A significant step towards developing a digital strategy that leverages new technologies to work smarter, better, and quicker, ultimately providing improved services.
How healthcare and AI merge together
In the healthcare sector, generative AI and other AI technologies are poised to bring transformative changes in several key areas:
Personalized Medicine: Generative AI can analyse vast amounts of patient data, including genetic information, to create personalized treatment plans. This approach can lead to more effective therapies tailored to individual patients’ needs.
Drug Discovery and Development: AI technologies can significantly speed up the drug discovery process by predicting how different compounds will interact with biological targets. Generative AI can design new molecules with desired properties, reducing the time and cost associated with bringing new drugs to market
Medical Imaging and Diagnostics: AI can enhance the accuracy of medical imaging by identifying patterns and anomalies that may be missed by human eyes. Generative AI can also create synthetic medical images to train diagnostic models, improving their performance and reliability
Virtual Health Assistants: AI-powered chatbots and virtual assistants can provide patients with instant access to medical information, answer health-related questions, and even assist in managing chronic conditions. These tools can improve patient engagement and reduce the burden on healthcare providers
Operational Efficiency: AI can optimize administrative tasks, such as scheduling, billing, and resource allocation, allowing healthcare professionals to focus more on patient care. Generative AI can also automate the creation of clinical documentation, saving time and reducing errors
Predictive Analytics: AI technologies can analyse historical data to predict future health trends and outcomes. This capability can help healthcare providers anticipate and prevent potential health issues, leading to better patient outcomes and more efficient use of resources
Overall, the integration of generative AI and other AI technologies in healthcare holds the promise of revolutionizing the industry by enhancing patient care, accelerating research and development, and improving operational efficiency.
Investment landscape in a life science sector
Key investment opportunities that are driving innovation and growth
Digital Business Initiatives: Investments in digital business transformation, including customer experience (CX), advanced analytics, and cloud platforms, are significant. These areas have consistently attracted funding due to their potential to enhance operational efficiency and drive growth.
Cyber/Information Security: As the life sciences sector increasingly relies on digital technologies, ensuring the security of data and systems has become paramount. Investments in cybersecurity are crucial to protect sensitive information and maintain trust.
Artificial Intelligence and Machine Learning: AI and ML technologies are being leveraged to accelerate drug discovery, optimize clinical trials, and improve patient outcomes. These technologies offer substantial opportunities for innovation and efficiency in the life sciences sector.
Precision Medicine: Advances in precision medicine, which tailors treatments to individual patients based on genetic, environmental, and lifestyle factors, are transforming healthcare. Investments in this area are expected to grow as the demand for personalized healthcare solutions increases.
Quantum Computing: Quantum computing holds the potential to revolutionize various aspects of life sciences, including drug discovery and materials science. Companies are exploring quantum applications to solve complex problems that are currently beyond the reach of classical computers.
Sustainability and Green Technologies: Investments in sustainable practices and green technologies are becoming increasingly important. This includes efforts to reduce the environmental impact of manufacturing processes and develop eco-friendly products.
AI in Search and Evaluation for Business Development
Utilizing AI in business development allows organizations to refine their marketing strategies, expand market share, discover new markets, and make informed product development decisions. Exploring AI’s distinctive value proposition for business development, showcasing where AI-driven technologies are making the most significant impact present how data-driven businesses are leveraging AI for innovation and sustainable growth.
Stories to learn more
Roundtable expert pool Interdisciplinary Expert Pool addressing specific questions and challenges in AI development
A roundtable expert pool, to discuss the results of the Interdisciplinary Expert Pool for NLU project, involving collaboration between humanities and social sciences researchers, civil society representatives, and addressing specific questions and challenges in AI development.
The development of large language models prompts more challenges than purely technological ones. Questions of data, representation, fairness, equality, and ethics are implicit and relevant to all projects and workstream in an interdisciplinary setting.
A Digital Platform for Precision Recycling of Medtech Waste
The increasing volume of medical technology (medtech) waste poses significant environmental challenges. To address this issue, a Digital Platform for Precision Recycling of Medtech Waste can be proposed. An innovative platform which aims to enhance the recyclability of medical product waste by leveraging advanced technologies such as artificial intelligence (AI) and data analytics.
The primary objective of the digital platform would be to improve the efficiency and effectiveness of recycling processes for medtech waste. By utilizing AI and data analytics, the platform will enable precise identification, sorting, and processing of various types of medical waste, ensuring that valuable materials are recovered and reused while minimizing environmental impact.
Key Features:
- AI-Powered Identification and Sorting: The platform will employ AI algorithms to accurately identify and categorize different types of medtech waste. This will facilitate the sorting process, ensuring that recyclable materials are separated from non-recyclable ones.
- Data-Driven Decision Making: By analyzing data from various sources, the platform will provide insights into the most effective recycling methods for different types of medtech waste. This will help optimize recycling processes and improve overall efficiency.
- Real-Time Monitoring and Reporting: The platform will offer real-time monitoring of recycling operations, allowing stakeholders to track progress and identify areas for improvement. Detailed reports will be generated to provide transparency and accountability.
- Collaboration and Integration: The platform will facilitate collaboration between various stakeholders, including healthcare providers, recycling companies, and regulatory bodies. It will also integrate with existing waste management systems to ensure seamless operations.
Benefits:
- Environmental Impact: By improving the recyclability of medtech waste, the platform will help reduce the environmental footprint of the healthcare industry. This will contribute to sustainability goals and support the transition to a circular economy.
- Cost Savings: Efficient recycling processes will lead to cost savings for healthcare providers and recycling companies. By recovering valuable materials, the platform will create economic opportunities and reduce the need for raw materials.
- Regulatory Compliance: The platform will help healthcare providers and recycling companies comply with regulatory requirements related to medical waste management. This will ensure that operations are conducted in a safe and environmentally responsible manner.
Conclusion: A Digital Platform for Precision Recycling of Medtech Waste would represent a significant step forward in addressing the environmental challenges posed by medical technology waste. By leveraging advanced technologies and fostering collaboration, the platform would enhance the efficiency and effectiveness of recycling processes, contributing to a more sustainable and circular healthcare industry.
Talentattraction – Investment opportunities in a Swedish biotech and digital health arena
Initiatives aimed at attracting talent and exploring investment opportunities within the Swedish biotech and digital health sectors is key. Efforts have focused on creating a conducive environment for innovation and collaboration, leveraging Sweden’s strong position in these fields.
A key initiative is Talent Attraction. Attracting top talent and fostering partnerships with health tech companies. Identifying key areas: Medical device technologies, quantum computing, and continuous manufacturing.
Investment opportunities in the Swedish biotech and digital health arena are provided. Our efforts include identifying and promoting investment prospects, facilitating networking opportunities, and supporting the growth of innovative companies in these sectors. By creating a supportive ecosystem, we aim to drive advancements in healthcare and digital health technologies, ultimately contributing to improved patient outcomes and economic growth.
Femtech Innovation – Hack Her Health
Spearheading the HackHERHealth initiative to address the significant gender disparities in healthcare, a must to drive innovation! Recognizing that women represent only 41% of clinical trial participants, aiming to bridge the gap in gender-specific healthcare. Historically, medical solutions and devices have been designed based on male physiology, leading to increased risks and decreased effectiveness for women. Women face a 50-75% higher risk of adverse drug reactions and unique challenges in cardiovascular disease, underscoring the need for tailored medical research and treatment approaches specific to women’s health.
Under my leadership, the initiative focused on various challenges such as neurodiversity, endometriosis, obesity, and more. Working closely with the team to define and prioritize these challenges, ensuring that we developed effective solutions.
NVIDIA Computational capability in a biotech setting – whats the future of LLMs in our sector
NVIDIA’s computational capabilities are revolutionizing the biotech sector, providing unprecedented power and efficiency for various applications. In a biotech setting, NVIDIA’s supercomputers, such as the “super-pod” capabilities, are being utilized to accelerate drug discovery and development. For instance, Bristol-Myers Squibb (BMS) has an NVIDIA super-pod capability and is conducting an AI co-lab with Vant AI to accelerate Molecular Glue Drug Discovery as small molecule therapeutics.
One notable example is the collaboration between the Novo Nordisk Foundation and NVIDIA to launch a visionary AI research center in Denmark. This center, funded by a $100 million investment, aims to elevate Denmark’s researchers and innovators to the next level by leveraging one of the world’s most powerful AI supercomputers. Additionally, NVIDIA’s Tokyo-1 supercomputer is being used by leading Japanese pharmaceutical companies to accelerate drug discovery, with plans to make it accessible to medical-device companies and startups.
The future of Large Language Models (LLMs) in the biotech sector is incredibly promising. NVIDIA has introduced the “NVIDIA AI Foundations” suite of cloud services, which includes the NVIDIA NeMo language service and the NVIDIA Picasso image, video, and 3D service. These solutions enable businesses to build custom generative AI applications for various use cases, such as intelligent chat, customer assistance, professional content creation, and digital simulation3. By utilizing these services, biotech companies can develop tailored LLMs and generative AI models to enhance their research and development processes.
Generative AI is set to become a cornerstone in drug discovery and design, offering unprecedented efficiency and innovation. For example, AI tools can sift through complex biological data to identify potential biomarkers for diseases, aiding in the development of targeted therapies4. Additionally, generative AI can help identify patient subgroups most likely to benefit from a new drug, leading to more effective and personalized clinical trials.
Overall, NVIDIA’s computational capabilities and the future of LLMs in the biotech sector are poised to drive significant advancements in drug discovery, personalized medicine, and overall healthcare innovation. By leveraging these technologies, biotech companies can accelerate their research and development efforts, ultimately improving patient outcomes and transforming the healthcare landscape.
Whats up at SLUSH? The worlds largest gathering of VC
SLUSH 2023 was a vibrant and dynamic event that brought together key stakeholders in the healthcare start-up ecosystem. The event, held in Helsinki, focused on fostering collaboration and innovation to address complex health and healthcare challenges. The partnership between AstraZeneca and SLUSH aimed to create groundbreaking partnerships, drive diversity and inclusion, and encourage the development of purpose-driven companies in the healthcare sector.
Key highlights included the SLUSH 100 Startup Competition, where entrepreneurs had the chance to win a €1 million investment from General Catalyst and Cherry Ventures. The event also featured workshops, mentoring sessions, and networking opportunities, providing a platform for aspiring entrepreneurs to connect with industry leaders and investors.
Overall, SLUSH 2023 was a significant event for the European innovation landscape, emphasizing the importance of collaboration and innovation in driving the future of healthcare.
AI advisory board in regional healthcare
As a member of the AI advisory board in regional healthcare, I play a pivotal role in leveraging AI, big data, and genomics technology to enhance healthcare capabilities. My work involves collaborating with leading healthcare organizations and innovators to improve the standard of care for patients, particularly in areas such as diabetes, heart disease, and cancer.
One of my key contributions is the development of digital platforms that facilitate effective ecosystem collaboration. These platforms enable seamless service delivery and execution of cross-organizational projects, fostering a collaborative environment for growth companies in biotechnology, digital health, and more.
My efforts are also focused on supporting start-ups and innovation centers, providing them with access to world-class infrastructure and expertise. This includes initiatives like the 360° approach in developing and supporting start-ups, as well as the creation of mobile applications for specific healthcare needs.
Overall, my work on the AI advisory board is instrumental in driving innovation and improving healthcare outcomes in the region. By bringing together relevant stakeholders and leveraging advanced technologies, I help reimagine the healthcare ecosystem and deliver valuable benefits to patients.
IT Leadership and how the ecosystem evolves and attract the partners of the future
IT Leadership plays a crucial role in shaping the future of technology and business. As the digital landscape continues to evolve, IT leaders must adapt and innovate to stay ahead. The ecosystem of IT leadership is dynamic, involving collaboration across various departments and external partners to drive greater business value.
One key aspect of this evolution is the development of digital platforms that facilitate effective ecosystem collaboration. These platforms enable seamless service delivery, execution of cross-organizational projects, and the generation of start-ups. By leveraging digital technologies, IT leaders can catalyze innovation and drive exploration of new science and technology horizons12.
To attract the partners of the future, IT leaders must focus on building pathways to external services and capabilities that are not yet available internally. This involves defining ecosystem investments that go beyond traditional business development and include opportunities in digital health, commercialization, and more34.
In summary, IT leadership is about fostering an environment of collaboration and innovation, ensuring that the organization is well-equipped to meet future challenges and seize new opportunities. By doing so, IT leaders can attract and retain valuable partners, driving the organization towards sustained success.
Board membership and steering of investments in a digital healthcare business evolvement
Board membership and steering of investments play a crucial role in the evolution of digital healthcare businesses. The board members are responsible for providing strategic direction, ensuring effective governance, and overseeing the allocation of resources to various projects. Their expertise and guidance help in making informed decisions that drive innovation and growth in the digital healthcare sector.
In the context of digital healthcare, investments are directed towards the development and implementation of advanced technologies, such as electronic health records (EHRs), telemedicine platforms, and mobile health applications. These investments aim to enhance patient care, improve operational efficiency, and ensure data security and privacy. The board’s role in steering these investments involves evaluating potential opportunities, assessing risks, and ensuring that the investments align with the organization’s overall goals and objectives.
Effective board governance and strategic investment decisions are essential for the successful transformation of healthcare services in the digital age. By leveraging their collective expertise, board members can help digital healthcare businesses navigate the complexities of the industry and achieve sustainable growth.
What do you think of when talking about AI in the Drug discovery and drug development process?
A great day with the students at the Medicinal Chemistry master program at Lund University.
A lot of thoughts and questions, and a fun and creative environment to be in.
Tech stack, Transformers and HealthTech
Thanks Ödgärd Andersson and Zenseact for highlight the importance of the stack. An interesting day discussing transformers, talent development and opportunities. Also, to put the lenses of HealthTech on the developments made the ways sectors convergence shine up.
Reflecting on AI with the Life Science experts of the future
Today I got the opportunity to talk about AI in the Drug Discovery and Development process at Lund University. Sharing a few reflections in the audience here.
AI as a driver for future business models in Medtech and Pharma
A day focused on innovation, in an Healthcare setting and with the opportunities and challenges with the development of Generative Pre-trained Transformers (GPTs) and AI models behind.
Around digital health technologies. How to improve data analytics, and enhance the patient journey across the continuum of care.
Zhangjiang Science City & GoCo Health Innovation City
Together we bring up the unexpected. Curious on new experties and network, a culture of dare to share.
Lab data and new AI algorithms combined with a team of experts
A plethora of scientific instruments, their data and development of novel AI algorithms for data insights
Sector convergence in a local setting, where the mobility industry look to dare to share with the medtech sector
A team presenting the mix of agile project management, ideation sparks, talent attraction and onboarding of the acquired skillsets⭐️
Brand the ecosystems boosting sector convergence
Data driven lab
Employer Branding
IT Networking in Sector Convergence settings
The future of business is digital
Integrating lab tools and workflows to aid scientists and improve outcomes
DNA and RNA sequencing and a drive for technologies enabling
Due Diligence around digital maturity
A setup of forums, all leading ahead on the digital path of biotech and life science businesses.
Data sharing as a means for catalyzing Life Science innovation
There is a lot of data out there, and a lot of hurdles to share and drive insights and new innovations. The need to catalyze HealthTech and Life Science innovation is as high as ever, and the opportunity to do so as well. We can give opportunities for Generative AI builds, we can drive Business needs with data, but most importantly we can reach out to patients to find more personalized medicines and better treatment.
Large Language Models such as chat-GPT facilitating but also driving innovation
How we see information and take it into decision making is super complex. GPTs process information with both speed, accuracy and built in Artificial Intelligence. This mix can both help us not only to translate information such as text or images, but to facilitate how we see it in alternative ways, and in addition drive how we create value in innovative ways. This house across sectors, life sciences, construction, production etc.
Sector convergence
Attrributes
Talent Attraction and Data Analytics
How do we attract the brilliant minds in our areas of interest? And how do we ensure we can widen our ability and jointly create and capture the value from the joint forces of brilliant minds. Today the future talents visited us and we are lucky enough to be able to attract them and get to work with them. Be curious and open with your know how, then the possibility will come.
The second angle of today is the specific expertise in data stewardship and data analytics. The use of data to gain insights creating joint value for patients, researchers and businesses has only just began…