Difference between revisions of "Cocktail bar: personalised medicine"
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===2010-2015=== | ===2010-2015=== | ||
The pace of aging | The pace of aging had accelated globally especially in more developed countries. By 2015, old people made up around 18% of the population in the developed countries. <br> | ||
By 2015, old people | |||
Concerned with health care system adoptability, the fact that old-age diseases are often very complex and the burden of the cronicle diseases of old people on the whole society, governments started initiatives to ask pharma companies to put efforts into old-age diseases research to elivate the medical system burdens in the society. <br> | |||
to | |||
Pharma R&D processes were under huge pressure to improve time-to-market and profitability. Since governments saw the need for shorter regulatory paths in view of largely increasing health service costs, they started to look for ways to shorten the regulatory requirements. <br> | |||
With the help of IT and internet and raising awareness from the aging population, people were paying more attention to their own health care and maintenance of their health. They were obtaining a lot of medical and medicine information from websites and played a more proactive role in managing their own health. <br> | |||
Meanwhile, big pharma research started to focus more on biomarkers and biotech-based research. This life science approach was fastly evolving, also due to the numerous biotech-start-ups in these fields, with which the big pharma started to cooperate closely. With help of increasing computational power of computers and the uncovering of the human genome in the preceeding years, biomarkers of diseases of a higher complexity could be identified and could be analysed on their prediction efficiency. <br> | |||
References: | References: | ||
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===2015-2020=== | ===2015-2020=== | ||
By year 2020, over 719 million of world population was over age of 65. | By year 2020, over 719 million of world population was over the age of 65. | ||
With the leap of biotech and generic,treatments were matched with patients more effectively through the development | With the leap of biotech and generic, treatments were matched with patients more effectively through the development of new genetic tests and medicines that are targeted to individual's genetic profile, using biomarkers to make these determinations. <br> | ||
of new genetic tests and medicines that are targeted to individual's genetic profile, using biomarkers to make | |||
these determinations. | |||
The research of Pharma also looked at synergies between already existing drugs and started to selectively develop new drugs on complementary basis, so that personalisation of medicine could take a leap. The drug development was very much powered by an increasing number of computer modeling programs, which saved pharmaceutical industry a large part of their development costs. <br> | |||
Also governmental actions on shortening the regulatory paths was starting to be fruitful, since the modeling of the whole biological system in the body made it easier to predict adverse effects of new types of medicines or of combinations of drugs. The regulatory path of medicine could therefore reliably be shortened without increasing the risk for the general population. <br> | |||
References: | References: | ||
| Line 45: | Line 34: | ||
===2020-2025=== | ===2020-2025=== | ||
Aging population is now more than 20% of the world population. With the biotech and generic drugs breakthough | |||
many people can enjoy more personalised medicines according to the therapeutic drug montoring and the responsiveness to the drugs. | |||
Regulatory process requirements were having a beneficial effect on R&D in pharmaceutical industry, significantly lowering the cost of developing new medicine. This enabled pharmaceutical industry to fully let go of the blockbuster system and focus much more on developing medicines that would have a lower volume of sales. | |||
It enabled development of new drugs that were much more efficient in treating complex diseases, like cancer, artritis, and alzheimers. The quality of life of people suffering from chonical diseases increased and the number of succesfull treatments also increased, thereby lowering the burden on the health system, whilst pharma industry was profitable in providing the treatments. | |||
Latest revision as of 06:12, 17 October 2009
Work under construction. In case you have any questions, additions or comments, please do not edit these pages, but you are more than welcome to contact us.
Selfcare scenario, with personalised medicine and focus on prevention, mainly driven by ageing population
Developments in time
2010-2015
The pace of aging had accelated globally especially in more developed countries. By 2015, old people made up around 18% of the population in the developed countries.
Concerned with health care system adoptability, the fact that old-age diseases are often very complex and the burden of the cronicle diseases of old people on the whole society, governments started initiatives to ask pharma companies to put efforts into old-age diseases research to elivate the medical system burdens in the society.
Pharma R&D processes were under huge pressure to improve time-to-market and profitability. Since governments saw the need for shorter regulatory paths in view of largely increasing health service costs, they started to look for ways to shorten the regulatory requirements.
With the help of IT and internet and raising awareness from the aging population, people were paying more attention to their own health care and maintenance of their health. They were obtaining a lot of medical and medicine information from websites and played a more proactive role in managing their own health.
Meanwhile, big pharma research started to focus more on biomarkers and biotech-based research. This life science approach was fastly evolving, also due to the numerous biotech-start-ups in these fields, with which the big pharma started to cooperate closely. With help of increasing computational power of computers and the uncovering of the human genome in the preceeding years, biomarkers of diseases of a higher complexity could be identified and could be analysed on their prediction efficiency.
References: http://longevity.stanford.edu/myworld/articles/populationaging
http://www.bioworld.com/img/S08431_TOC.pdf
2015-2020
By year 2020, over 719 million of world population was over the age of 65.
With the leap of biotech and generic, treatments were matched with patients more effectively through the development of new genetic tests and medicines that are targeted to individual's genetic profile, using biomarkers to make these determinations.
The research of Pharma also looked at synergies between already existing drugs and started to selectively develop new drugs on complementary basis, so that personalisation of medicine could take a leap. The drug development was very much powered by an increasing number of computer modeling programs, which saved pharmaceutical industry a large part of their development costs.
Also governmental actions on shortening the regulatory paths was starting to be fruitful, since the modeling of the whole biological system in the body made it easier to predict adverse effects of new types of medicines or of combinations of drugs. The regulatory path of medicine could therefore reliably be shortened without increasing the risk for the general population.
2020-2025
Aging population is now more than 20% of the world population. With the biotech and generic drugs breakthough many people can enjoy more personalised medicines according to the therapeutic drug montoring and the responsiveness to the drugs.
Regulatory process requirements were having a beneficial effect on R&D in pharmaceutical industry, significantly lowering the cost of developing new medicine. This enabled pharmaceutical industry to fully let go of the blockbuster system and focus much more on developing medicines that would have a lower volume of sales.
It enabled development of new drugs that were much more efficient in treating complex diseases, like cancer, artritis, and alzheimers. The quality of life of people suffering from chonical diseases increased and the number of succesfull treatments also increased, thereby lowering the burden on the health system, whilst pharma industry was profitable in providing the treatments.