1598748780
How AI Can Improve Drug Development Amidst the Search for a COVID-19 Cure
The use of Artificial Intelligence (AI) is surging, and one area in which its use is even more important in 2020 – the year of a global pandemic – is in health technology, or healthtech.
Berlin-based, non-profit think tank dGen has just released a new report, “AI, Privacy, and Genomics: The Next Era of Drug Design”, which looks at the issue of privacy and access to genetic data for companies using AI to speed up and improve drug design.
With articles about work on a vaccine for COVID-19 flooding newspapers every day, most people are now more aware of the typical timelines involved in creating new drugs. They certainly don’t appear overnight. As the dGen report states, “The average drug today takes 10-12 years and cost $2 billion.” However, the arrival of the new coronavirus has forced researchers to think more in terms of 12-18 months, which is like exchanging a leisurely world cruise for supersonic flight.
Enter AI, which in 2020 is only just entering drug R&D where it is being used to test and improve candidate drugs before they can be fully accredited by regulators, such as the FDA in the USA.
But there is one area of concern: genetic information is central to many AI-enabled drug discovery startups. To expand this innovation, a number of issues with using genetic data must be resolved. The dGen report lists these as:
- ownership
- secure storage
- availability to multiple research parties.
In order for all of us to accept the wider use of AI in drug design, privacy concerns must be addressed using the privacy-preserving techniques in machine learning. These allow researchers to process genetic material without fully revealing its source.
While this is crucial for privacy, the techniques do not address the issue of ownership, or ways to audit the system. What the dGen report proposes is a decentralized pan-European biobank network that makes information available to researchers, but all access requests have to be logged. In that way, we all know who has looked at our genetic data. Furthermore, it would allow us as individuals to grant or deny these requests and track the use of our information.
dGen’s Top Predictions for 2030
Based on better privacy-preserving technologies and an access network, dGen’s top predictions for 2030 are:
- Better collaboration networks will emerge
- Genetic privacy laws will be overhauled
- AI will become a fundamental part of drug discovery
- Pharmaceutical giants won’t be toppled, but they won’t get out unscathed as biotech startups take the field
The Views of Industry Leaders
It is also interesting to note the responses to the dGen report from those working in AI and healthtech. The think tank interviewed industry leaders from Aidence, Gero, Alphanosos, e-Estonia, Qunatlib and Turbine amongst others.
Maxim Kholin, Gero Co-Founder said,‘We believe that AI can accelerate the drug discovery process by proper understanding of human diseases from large biomedical data. The data-driven approach should help establish the genetic determinants and molecular markers of the disease’.
#covid19 #healthtech #artificial-intelligence #vaccines #machine-learning #pharmaceutical #ai-in-medicine #ai
What is GEEK
Buddha Community
1598748780
How AI Can Improve Drug Development Amidst the Search for a COVID-19 Cure
The use of Artificial Intelligence (AI) is surging, and one area in which its use is even more important in 2020 – the year of a global pandemic – is in health technology, or healthtech.
Berlin-based, non-profit think tank dGen has just released a new report, “AI, Privacy, and Genomics: The Next Era of Drug Design”, which looks at the issue of privacy and access to genetic data for companies using AI to speed up and improve drug design.
With articles about work on a vaccine for COVID-19 flooding newspapers every day, most people are now more aware of the typical timelines involved in creating new drugs. They certainly don’t appear overnight. As the dGen report states, “The average drug today takes 10-12 years and cost $2 billion.” However, the arrival of the new coronavirus has forced researchers to think more in terms of 12-18 months, which is like exchanging a leisurely world cruise for supersonic flight.
Enter AI, which in 2020 is only just entering drug R&D where it is being used to test and improve candidate drugs before they can be fully accredited by regulators, such as the FDA in the USA.
But there is one area of concern: genetic information is central to many AI-enabled drug discovery startups. To expand this innovation, a number of issues with using genetic data must be resolved. The dGen report lists these as:
- ownership
- secure storage
- availability to multiple research parties.
In order for all of us to accept the wider use of AI in drug design, privacy concerns must be addressed using the privacy-preserving techniques in machine learning. These allow researchers to process genetic material without fully revealing its source.
While this is crucial for privacy, the techniques do not address the issue of ownership, or ways to audit the system. What the dGen report proposes is a decentralized pan-European biobank network that makes information available to researchers, but all access requests have to be logged. In that way, we all know who has looked at our genetic data. Furthermore, it would allow us as individuals to grant or deny these requests and track the use of our information.
dGen’s Top Predictions for 2030
Based on better privacy-preserving technologies and an access network, dGen’s top predictions for 2030 are:
- Better collaboration networks will emerge
- Genetic privacy laws will be overhauled
- AI will become a fundamental part of drug discovery
- Pharmaceutical giants won’t be toppled, but they won’t get out unscathed as biotech startups take the field
The Views of Industry Leaders
It is also interesting to note the responses to the dGen report from those working in AI and healthtech. The think tank interviewed industry leaders from Aidence, Gero, Alphanosos, e-Estonia, Qunatlib and Turbine amongst others.
Maxim Kholin, Gero Co-Founder said,‘We believe that AI can accelerate the drug discovery process by proper understanding of human diseases from large biomedical data. The data-driven approach should help establish the genetic determinants and molecular markers of the disease’.
#covid19 #healthtech #artificial-intelligence #vaccines #machine-learning #pharmaceutical #ai-in-medicine #ai
1620127560
Data Scientist Creates Python Script To Track Available Slots For Covid Vaccinations
Bhavesh Bhatt, Data Scientist from Fractal Analytics posted that he has created a Python script that checks the available slots for Covid-19 vaccination centres from CoWIN API in India. He has also shared the GitHub link to the script.
The YouTube content creator posted, “Tracking available slots for Covid-19 Vaccination Centers in India on the CoWIN website can be a bit strenuous.” “I have created a Python script which checks the available slots for Covid-19 vaccination centres from CoWIN API in India. I also plan to add features in this script of booking a slot using the API directly,” he added.
We asked Bhatt how did the idea come to fruition, he said, “Registration for Covid vaccines for those above 18 started on 28th of April. When I was going through the CoWIN website – https://www.cowin.gov.in/home, I found it hard to navigate and find empty slots across different pin codes near my residence. On the site itself, I discovered public APIs shared by the government [https://apisetu.gov.in/public/marketplace/api/cowin] so I decided to play around with it and that’s how I came up with the script.”
Talking about the Python script, Bhatt mentioned that he used just 2 simple python libraries to create the Python script, which is datetime and requests. The first part of the code helps the end-user to discover a unique district_id. “Once he has the district_id, he has to input the data range for which he wants to check availability which is where the 2nd part of the script comes in handy,” Bhatt added.
#news #covid centre #covid news #covid news india #covid python #covid tracing #covid tracker #covid vaccine #covid-19 news #data scientist #python #python script
1595059664
How long does it take to develop/build an app?
With more of us using smartphones, the popularity of mobile applications has exploded. In the digital era, the number of people looking for products and services online is growing rapidly. Smartphone owners look for mobile applications that give them quick access to companies’ products and services. As a result, mobile apps provide customers with a lot of benefits in just one device.
Likewise, companies use mobile apps to increase customer loyalty and improve their services. Mobile Developers are in high demand as companies use apps not only to create brand awareness but also to gather information. For that reason, mobile apps are used as tools to collect valuable data from customers to help companies improve their offer.
There are many types of mobile applications, each with its own advantages. For example, native apps perform better, while web apps don’t need to be customized for the platform or operating system (OS). Likewise, hybrid apps provide users with comfortable user experience. However, you may be wondering how long it takes to develop an app.
To give you an idea of how long the app development process takes, here’s a short guide.
App Idea & Research
_Average time spent: two to five weeks _
This is the initial stage and a crucial step in setting the project in the right direction. In this stage, you brainstorm ideas and select the best one. Apart from that, you’ll need to do some research to see if your idea is viable. Remember that coming up with an idea is easy; the hard part is to make it a reality.
All your ideas may seem viable, but you still have to run some tests to keep it as real as possible. For that reason, when Web Developers are building a web app, they analyze the available ideas to see which one is the best match for the targeted audience.
Targeting the right audience is crucial when you are developing an app. It saves time when shaping the app in the right direction as you have a clear set of objectives. Likewise, analyzing how the app affects the market is essential. During the research process, App Developers must gather information about potential competitors and threats. This helps the app owners develop strategies to tackle difficulties that come up after the launch.
The research process can take several weeks, but it determines how successful your app can be. For that reason, you must take your time to know all the weaknesses and strengths of the competitors, possible app strategies, and targeted audience.
The outcomes of this stage are app prototypes and the minimum feasible product.
#android app #frontend #ios app #minimum viable product (mvp) #mobile app development #web development #android app development #app development #app development for ios and android #app development process #ios and android app development #ios app development #stages in app development
1625477099
IoT vs AI: Top Differences to Know Between Two Strong Rivals
If I talk about trending technologies, then both Artificial Intelligence (AI) vs Internet of Things (IoT) are currently at the top of the list. Whether it is IoT or AI, both are giving neck-to-neck competition; this is why nowadays businesses are inclined to embrace both technologies in software development.
• 83% of companies have enhanced their efficiency by introducing IoT technology.
• Around 79% of executives consider adopting AI in the industry will make their work effective and more manageable.
Now the question is, what is the difference between AI and IoT. To know the same, read further…
What is Internet of Things (IoT)?
The Internet of Things (IoT) is a system of interrelated, internet-connected objects that can accumulate and convey data over a wireless network without human interference.
Famous companies using IoT: Google, Amazon, Microsoft, and more
Worldwide, the market for Internet of things (IoT) end-user solutions is anticipated to expand around $1.6 trillion in size by 2025.
IoT is a trend for mobile app development, but when it comes to integrating IoT technology in the business or app development process, then it is pretty complex, so to make this process easier, you can avail of IoT software development services from trustworthy IoT app development company India.
**Benefits of Internet of Things (IoT) in Businesses
**
Here I have mentioned the key benefits of using IoT in business. If your business has till now not adopted the IoT technology, then include it; this will help you make the business process easier.
Reduction of operating costs: IoT solutions can help enterprises cut costs and maintain a competing advantage. In the manufacturing sector, IoT devices are employed to monitor equipment and decrease downtime by predicting misalignment on the production line.
Understanding of consumer behavior: Understanding consumer choices and behavior can help businesses attain success, and with IoT grasping such important things are possible. Using IoT, businesses can gather, monitor, and examine data from social media, video surveillance, mobile, and internet usage.
Improved customer service and retention: Using IoT, businesses can collect user-specific data via smart devices and understand customers’ expectations and behavior. Doing so can help businesses improve customer service by facilitating follow-ups after sales, such as automatic tracking and customer retention.
Improved safety: Using IoT technology in various devices such as surveillance cameras, motion sensors, and other monitoring devices can help businesses form products offering high-level security.
Disadvantages of IoT
Well, all things can’t be wholly perfect same like that IoT is also having few drawbacks stated here:
Security Flaws: IoT technology gathers data from various sources, and this is why the technology lacks in offering high-level security.
Associated costs: Implementation of IoT infrastructure in a business intends to build a huge network including multiple smart devices, a massive power supply grid, and a communication network. Doing all this may require high costs.
Network dependence: The key feature of the Internet of Things is the enormous amount of interconnections between multiple devices and access to the worldwide network; these networks depend on each other means if one shows the error, then others working will also get affected.
These disadvantages can be converted into benefits, but you need to apply an extraordinary strategy for that. And only experts can do this thing in a better way, so, in order to leave these IoT cons behind, hire IoT developers working in the topmost IoT development companies.
**What is Artificial Intelligence (AI)?
**
Artificial Intelligence(AI) relates to the simulation of human intelligence in machines designed to ponder like humans and imitate their actions. AI can be employed as any machine that displays traits correlated with a human mind, such as learning, understanding, and problem-resolving.
Worldwide, the Artificial Intelligence (AI) software market is projected to grow swiftly in the coming years, reaching around $126 billion by 2025.
To make efficient use of AI in your business process, avail of Artificial Intelligence development services from the top Artificial Intelligence development company. Doing so will make adequate use of AI solutions.
Benefits of Artificial Intelligence in Businesses
Here I have mentioned a few factors which can help you know why AI is important for business and how it is helping various industry verticals in growing.
Real-Time Analytics: Using AI, businesses can process a massive amount of data and render it in real-time. It is one of the topmost advantages of AI for business. This approach enables enterprises to make vital decisions fast.
Better Customer Experience: AI-based chatbots are competent in rendering round-the-clock user request support at any time. Better communication quality and shorter reply times help businesses improve existing customers’ loyalty and drag new ones.
Data Security Improvement: AI can successfully be utilized to recognize fraud efforts and illegal access to personal data; this is why most finance and banking industries use AI technology.
Predictive Analytics: AI technologies can manage the enormous amount of arrays, recognizing patterns and foretelling the future. Most businesses are interested in predicting things so that they can minimize the imminent risk and other things; these all things can be simply done with the help of AI.
Disadvantages of AI
The pointers mentioned here are few cons of Artificial Intelligence (AI). Well, you can lessen the effectiveness of AI cons, and for doing so, you can hire AI developers from the foremost AI development company.
Higher Costs: Introducing AI in app development is a time taking process, and it may also cost an immense deal of money. Moreover, it is also a complex task to develop AI integrated software programs.
No creativity: Well, with AI, you cannot do innovative things. AI is proficient in learning over time with pre-fed pieces of information and experiences, but it can’t act like a creative approach.
Make Humans Lazy: AI applications automate the bulk of slow and monotonous tasks. Since we do not have to remember things to resolve puzzles, and all this can make humans lazy.
AI vs IoT: Know The Difference Between AI and IoT
The aspects stated here will help you know the exact difference between AI and IoT. If, after reading the pointers, you are still confused about IoT and AI, then get connected with the experts working at the top-notch Artificial Intelligence development company (ValueCoders). Doing so will help you know which one will be best for your business, seeing the process and needs.
- Cloud Computing
AI is a highly strong software that can think, perform and learn from human instances. Well, Artificial Intelligence (AI) and the Internet of Things (IoT) are both complementary in performance, but IoT Cloud gives a pathway to handle data.
2. Procuring obtainable data
Artificial Intelligence (AI) understands, learns, improves its performance from mistakes. Moreover, it also helps in making efficient decisions making where IoT captures consequences on sensors that gather and store data whenever required.
3. Data
Artificial Intelligence has the capability of understanding the pattern and behaviors where the Internet of Things (IoT) is all about sensors.
4. Algorithm
AI is totally based on deep learning algorithms, which are gathered from multiple sources to produce the behavior of the system. IoT is utilized for building an algorithm to express the system’s behavior.
5. Behavior
AI is all about spontaneous reactions to receiving the input. At the same time, IoT stores predefined responses that are triggered utilizing the devices and are predefined by applying particular codes based on various algorithms.
ValueCoders includes a dedicated development team that can help you make adequate use of various technologies like AI, IoT, Machine Learning, Blockchain. So, if you are finding reliable solutions related to these technologies, get in touch with us.
Ending Word
Individually and collectively, IoT and AI will remain the best trends in the future. Each day a massive amount of data is produced, which is really hard to gather and understand, but all this is possible using IoT; similarly, there are various tasks which are complex for business to perform such as efficient decision-making, predicting behavior, but with AI such works can easily be performed.
Several differences and similarities are there in the functioning of both technologies, AI vs IoT. But both are very impactful if the potential of both technologies is correctly employed in the business process. In order to make adequate use of AI and IoT in business software development, hire AI developers in India or hire IoT developers working in one of the best AI development companies (ValueCoders).
#hire ai developers in india #hire ai developers #hire ai developer #iot developer #iot developers #iot development companies
1602979200
Developer Career Path: To Become a Team Lead or Stay a Developer?
For a developer, becoming a team leader can be a trap or open up opportunities for creating software. Two years ago, when I was a developer, I was thinking, “I want to be a team leader. It’s so cool, he’s in charge of everything and gets more money. It’s the next step after a senior.” Back then, no one could tell me how wrong I was. I had to find it out myself.
I Got to Be a Team Leader — Twice
I’m naturally very organized. Whatever I do, I try to put things in order, create systems and processes. So I’ve always been inclined to take on more responsibilities than just coding. My first startup job, let’s call it T, was complete chaos in terms of development processes.
Now I probably wouldn’t work in a place like that, but at the time, I enjoyed the vibe. Just imagine it — numerous clients and a team leader who set tasks to the developers in person (and often privately). We would often miss deadlines and had to work late. Once, my boss called and asked me to come back to work at 8 p.m. to finish one feature — all because the deadline was “the next morning.” But at T, we were a family.
We also did everything ourselves — or at least tried to. I’ll never forget how I had to install Ubuntu on a rack server that we got from one of our investors. When I would turn it on, it sounded like a helicopter taking off!
At T, I became a CTO and managed a team of 10 people. So it was my first experience as a team leader.
Then I came to work at D — as a developer. And it was so different in every way when it came to processes.
They employed classic Scrum with sprints, burndown charts, demos, story points, planning, and backlog grooming. I was amazed by the quality of processes, but at first, I was just coding and minding my own business. Then I became friends with the Scrum master. I would ask him lots of questions, and he would willingly answer them and recommend good books.
My favorite was Scrum and XP from the Trenches by Henrik Kniberg. The process at D was based on its methods. As a result, both managers and sellers knew when to expect the result.
Then I joined Skyeng, also as a developer. Unlike my other jobs, it excels at continuous integration with features shipped every day. Within my team, we used a Kanban-like method.
We were also lucky to have our team leader, Petya. At our F2F meetings, we could discuss anything, from missing deadlines to setting up a task tracker. Sometimes I would just give feedback or he would give me advice.
That’s how Petya got to know I’d had some management experience at T and learned Scrum at D.
So one day, he offered me to host a stand-up.
#software-development #developer #dev-team-leadership #agile-software-development #web-development #mobile-app-development #ios-development #android-development