Ask Puja Goyal a questionSign Up to our Clinical Trials questions and Answers Engine to ask questions, answer people's questions, and connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Ask Puja Goyal a question
Are drug clinical trials faster and less costly in Europe versus the USA due to the efficiencies and centralization of universal health care?
Puja Goyal
Generally speaking, no. The clinical trial sponsor is still responsible for medical care of the patients during the study. The costs of ancillary care to the patients (as opposed to the cost of the core treatment) is typically a minority share of the total cost of a clinical study, so even a 50% savRead more
Generally speaking, no. The clinical trial sponsor is still responsible for medical care of the patients during the study. The costs of ancillary care to the patients (as opposed to the cost of the core treatment) is typically a minority share of the total cost of a clinical study, so even a 50% savings might be a 5% reduction in the total study cost.
There can be some cost savings to conducting studies in Eastern European countries. But again, that’s less to do with single-payer healthcare and more because the going rates for physician stipends, site costs, and CRA salaries are lower.
See lessWill contract research organizations (CROs) play an increasing or decreasing role in pharmaceutical R&D over the next few years?
Puja Goyal
According to the Association of Clinical Research Organizations, CRO conduct more than 9,000 clinical trials in 140 countries involving nearly two million research subjects. 2015 revenue is estimated at $25.6 billion, representing about a third of total drug development spending. CROs employ approxiRead more
According to the Association of Clinical Research Organizations, CRO conduct more than 9,000 clinical trials in 140 countries involving nearly two million research subjects. 2015 revenue is estimated at $25.6 billion, representing about a third of total drug development spending. CROs employ approximately 110,000 people worldwide, and are reported by the Tufts Center for the Study of Drug Development (CSDD) to now have more clinical research staff than the pharma industry itself.
According to a report published by Infiniti Research Ltd, the CRO market is expected to grow at a CAGR of 9.8% over the period 2014-2019. Driving this growth is increased R&D spend by biopharm companies, along with an expanding pipeline of biologics to treat diseases such as diabetes, cancer, and genetic diseases.
See lessDo pharmaceutical companies outsource their research, or do they do it themselves in-house?
Puja Goyal
To answer your question, the pharmaceutical companies pursue both In-house or external R&D. Bigger companies are especially doing more R&D outside to reduce risks/costs and focus their efforts/budgets on only sure bets. Following factors affect the decision to perform research in-house/exterRead more
To answer your question, the pharmaceutical companies pursue both In-house or external R&D. Bigger companies are especially doing more R&D outside to reduce risks/costs and focus their efforts/budgets on only sure bets.
Following factors affect the decision to perform research in-house/externally:
There are different phases of research that can be done outside as well as different models of collaborations.
See lessHow do CROs choose sites for clinical trials?
Puja Goyal
When it comes to choosing sites for a clinical trial, it’s all about relationships. The relationship between sponsors, clinical research organizations, and study sites is the key to improving clinical trial performance.
When it comes to choosing sites for a clinical trial, it’s all about relationships. The relationship between sponsors, clinical research organizations, and study sites is the key to improving clinical trial performance.
See lessIs it worth registering as a member in the Indian society for clinical research?
Puja Goyal
Yes it is, to help all of the Native Americans. All minorities need to do their part in clinical trials so that future medicines have data to represent their tolerances and outcomes as well. Generally it's a white working male that participates. Each race react differently to medicines, so for betteRead more
Yes it is, to help all of the Native Americans. All minorities need to do their part in clinical trials so that future medicines have data to represent their tolerances and outcomes as well. Generally it’s a white working male that participates. Each race react differently to medicines, so for better medical treatment, participation in development is crucial.
See lessHow much will AI affect the pharmaceutical industry in the next 5 years? To what extent does the pharma industry already rely on AI?
Puja Goyal
Over the past 10 years we have seen an increasing amount of complexity in machine learning algorithms that are being applied to everyday uses, from internet searches to voice recognition and self-driving cars. Pharmaceutical research and development (R&D) has also seen a number of artificially iRead more
Over the past 10 years we have seen an increasing amount of complexity in machine learning algorithms that are being applied to everyday uses, from internet searches to voice recognition and self-driving cars. Pharmaceutical research and development (R&D) has also seen a number of artificially intelligent and machine learning developments take hold in the industry. Applying these methods to mine the growing amount of big data that is constantly being generated from all of the clinical trials taking way, not only enables us to learn from past data, but also to predict a molecule’s properties and efficacy in the future.
One of the latest machine learning algorithms that is making attention in the headlines is the deep learning (DL) platform, which consists of artificial neural networks (ANNs) with multiple layers of data to access. Recent publications suggest that these advanced algorithms may have advantages over traditional machine learning methods and offers a slight edge in predictive performance. Machine learning methods, such as DL, will apply across a wider array of endpoints in the near future, making predictions for advanced synthesis techniques, ADME/Tox studies, and even clinical trials themselves. Studies are also showing many other potential applications of deep learning and AI well beyond cheminformatics.
Another surprising fact is that the same algorithms we already use everyday, such as the ones for smartphones, voice recognition, and so on, are the same algorithms that we should be considering for cheminformatics, and other areas in the pharmaceutical industry. Large companies, such as Google, Amazon and Facebook, have actually been using deep learning and AI for years. In the near future, once AI is fully integrated into the drug development process, we will be able to see the benefits in research and development and healthcare in general.
See lessWhat are some good use cases for artificial Intelligence in healthcare?
Puja Goyal
Many industries have been disrupted by the influx of new technologies in the Information Age. Healthcare is no different. Here are some common ways AI is changing healthcare now and will in the future: 1. Managing Medical Records and Other Data - Since the first step in health care is compiling andRead more
Many industries have been disrupted by the influx of new technologies in the Information Age. Healthcare is no different. Here are some common ways AI is changing healthcare now and will in the future:
1. Managing Medical Records and Other Data – Since the first step in health care is compiling and analyzing information (like medical records and other past history), data management is the most widely used application of artificial intelligence and digital automation. Robots collect, store, re-format, and trace data to provide faster, more consistent access.
2. Treatment Design – Artificial intelligence systems have been created to analyze data – notes and reports from a patient’s file, external research, and clinical expertise – to help select the correct, individually customized treatment path.
3. Medication Management – The National Institutes of Health have created the AiCure app to monitor the use of medication by a patient. A smartphone’s webcam is partnered with AI to autonomously confirm that patients are taking their prescriptions and helps them manage their condition. Most common users could be people with serious medical conditions, patients who tend to go against doctor advice, and participants in clinical trials.
4. Precision Medicine – Genetics and genomics look for mutations and links to disease from the information in DNA. With the help of AI, body scans can spot cancer and vascular diseases early and predict the health issues people might face based on their genetics.
5. Health Monitoring – Wearable health trackers – like those from FitBit, Apple, Garmin and others – monitors heart rate and activity levels. They can send alerts to the user to get more exercise and can share this information to doctors (and AI systems) for additional data points on the needs and habits of patients.
See lessHow do I start learning artificial intelligence? Is it possible to get research work in the field of A.I? Are there open source projects where I can contribute?
Puja Goyal
Most AI research today is misguided; they have been trying to solve the wrong problem for sixty-five years to the tune of a million man-years. Solving the right problem is much easier and we should be done in about five years. This is a very good time to get into AI research... as long as you avoidRead more
Most AI research today is misguided; they have been trying to solve the wrong problem for sixty-five years to the tune of a million man-years. Solving the right problem is much easier and we should be done in about five years. This is a very good time to get into AI research… as long as you avoid almost everything that has been done in AI research to date, since very little of that actually contributes to finding the correct solution.
Step one is to realize that the human mind is not scientific. It is a result of evolution and excels at finding quick-and-dirty solutions to incompletely specified problems in almost zero time. Almost everything we do on a daily basis is done this way; this is what we use our brains for, and this is what an AI would have to be able to do. It’s called “Intuitive Understanding”.
Step two is to realize that Understanding requires the ability to know “What Matters”. What is relevant, and what is irrelevant to the situation at hand. The core unsolved problem in AI is to find a problem domain independent measure of “Saliency” – to know whether something matters or not. Several algorithms for domain-independent saliency are currently being evaluated by researchers in this area and some are showing some promise. This corner of AI research is where the action is.
See lessHow is artificial intelligence linked with biotech?
Puja Goyal
Though artificial intelligence and biotechnology have rarely anything in common, but their efforts have come along a long way and are helping each other by means of neural network, multi agent systems applied to food technology, agricultural and livestock production and renewable energy generation.Read more
Though artificial intelligence and biotechnology have rarely anything in common, but their efforts have come along a long way and are helping each other by means of neural network, multi agent systems applied to food technology, agricultural and livestock production and renewable energy generation.
Using Artificial Intelligence and Biotechnology is beneficial as well as productive. Here are some examples: –
• Usage of AI in the identification of targets and ligands in the early stage drug developments.
• Integrating AI into prosthetics to mimic human development.
• Development of AI classification technology to look for early signs of tumors.
And many more.
See lessApart from clinical diagnosis, what areas do you see machine intelligence and AI playing key roles in medicine going forward?
Puja Goyal
Diagnosis is the most obvious, and least likely area of medicine, to benefit hugely from AI in the next 10 years. The reasons for this are interesting and make a good deal of sense when considered carefully. They deserve a question/answer of their own. Since however you ask for the areas that will bRead more
Diagnosis is the most obvious, and least likely area of medicine, to benefit hugely from AI in the next 10 years. The reasons for this are interesting and make a good deal of sense when considered carefully. They deserve a question/answer of their own. Since however you ask for the areas that will be affected most prominently I’ll give you a couple of areas where I think there is real potential.
It is sometimes said that automation is for tasks that are dirty dangerous and repetitive. Medicine is just choc-a-bloc with that
See less