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Life Sciences, Pharmaceutics and ICT

[Wyoming - Forbes]

- The Key Characteristics of Living Beings

Key characteristics or functions of living beings are order, stimuli, reproduction, growth/development, regulation, homeostasis, and energy.

Order can include highly organized structures such as cells, tissues, organs, and organ systems; Interaction with the environment is shown by response to stimuli; The ability to reproduce, grow and develop are defining features of life; The concepts of biological regulation and maintenance of homeostasis are key to survival and define major properties of life. Organisms use energy to maintain their metabolic processes; Populations of organisms evolve to produce individuals that are adapted to their specific environment.

Biology is the study of life. Since life is such a broad topic, scientists break it down into several different levels of organization to make it easier to study. These levels start from the smallest unit of life and work up to the largest and most broad category. The levels, from smallest to largest, are: molecule, cell, tissue, organ, organ system, organism, population, community, ecosystem, biosphere.

- Life Sciences in the ICT Age

The ICT Age has arrived. We are in a stage where we have access to all information all the time. This is likely to have a great impact from our medical care but also our behavior and how we live our lives. Much of our software and data have moved from out of our desktop, yet they are accessible locally and remotely.

Life sciences and ICT are coming together to revolutionize scientific and medical discovery; comprising: acquisition, transmission, processing, storage and retrieval of biomedical and health information. The general computing trend is to leverage shared web resources and massive amounts of data over the Internet. 

- A New Era of Data-Driven Medicine

The foundation for a new era of data-driven medicine has been set by recent technological advances that enable the assessment and management of human health at an unprecedented level of resolution (high-definition medicine). Telemedicine, predictive diagnostics, wearable sensors and a host of new apps will transform how people manage their health. 

With today’s high-throughput sequencing technology, it’s much easier to generate genomic data than to transform it into information or knowledge that can improve human health. We are at the beginning of the genomics revolution. 

The promise of genomics is to revolutionize treatment of disease, to personalize treatment. The unprecedented abundance of medically relevant data (e.g. molecular, cellular, organismal, ecological, behavioral, clinical), from detailed information about genes and genetic diseases and the relative efficacy of drugs in diverse patient populations, to three-dimensional imaging of living cells giving researchers a more detailed and accurate spatial visualization of the interplay of cells and their components, is driving the use of quantitative methods in medicine.  


[Chicago - Hyatt Regency]

- Beyond Precision Medicine: High Definition Medicine

The foundation for a new era of data-driven medicine has been set by recent technological advances that enable the assessment and management of human health at an unprecedented level of resolution - what we refer to as high-definition medicine. Our ability to assess human health in high definition is enabled, in part, by advances in DNA sequencing, physiological and environmental monitoring, advanced imaging, and behavioral tracking. 

For example, recent advances have made 3D imaging (e.g., enabling 3D images of living organisms to be obtained with greater speed and precision) a valuable tool for many applications, such as cell biology, developmental biology, neuroscience and cancer research. These new approaches will improve our understanding of finding better diagnostics, treatments and therapies for diseases. 

- New Technologies are Accelerating Drug Discovery and Development

Many patients and their doctors wait for years before promising treatments become available. All too often, unforeseen side effects send researchers back to the drawing board, just when they thought they were close to bringing a new medication to market. It takes, on average, at least 10 years for a drug to make the journey from discovery to the marketplace at an average cost of $2.6 billion. The overall cost includes not only the development costs for drugs that successfully made it to market, but also for the drugs that failed along the way. 

Today, the likelihood that a drug entering clinical testing will eventually be approved is estimated to be much less (more than 12%). What researchers are learning is that by using certain technologies (for example, machine learning - training a machine to see more than we can, mining big data, deep text mining and analysis, sentiment analysis, facilitating collaborations across sectors and organizations, etc.), early in the drug-development process, they can identify issues that might cause a drug to fail early on, in many cases before the compound even goes into clinical testing. 

Then they can either modify the compound to address the issues, while maintaining the therapeutic effects, or make an early decision to no longer pursue the drug candidate, thereby averting a more expensive later stage failure. 


[More to come ...]

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