What makes a clinical investigation run smoothly?
In today’s conversation, you’ll hear from Jon Bergsteinsson as we speak about electronic data capture for clinical investigations.
Jon has a master’s degree in biomedical engineering and is the founder of Greenlight Guru Clinical (formerly SMART-TRIAL), which helps MedTech companies close the gap between their devices and clinical data. His valuable insights come from 10 years of experience in the MedTech clinical space plus a strong technical background.
Listen to today’s episode to hear what Jon has to say about using Electronic Data Capture (EDC) systems in clinical investigations, the importance of data quality and what that really means, the tools available for clinical investigations, and educating leadership about clinical investigations.
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Some of the highlights of this episode include:
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The biggest challenges companies face during clinical investigations
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What kinds of tools are available for clinical Investigations
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The relationship between data quality and formatting
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The impact a purpose-built tool has on a company
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The costs associated with clinical investigations
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Educating leadership about clinical operations
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What makes the best stand out
Links:
Memorable quotes from Jón I. Bergsteinsson:
“Data quality has everything to do with how you format your data.”
“The leadership just doesn’t have that much of an understanding of what clinical operations do, so they need to be educated.”
“When you have a person who’s very efficient, you can get 100 attributes in a couple of minutes.”
“Digital first is what sets the best from the rest.”
Transcript:
Etienne Nichols: Welcome back.
Today I get to speak with Jón Bergsteinsson once again from.
Well, he's from Greenlight Guru and he's working on the clinical side of things. So, there's a lot of discussion about that, but we don't have to go into that. We'll probably will at some point, but today I'd like to talk to him a little bit about electronic data capture.
And you've had him. We've had him on the podcast before, so he may be a familiar voice to you as well.
But I'll give him a chance just to give a. Give a little bit of his background and some of his expertise around clinical and, and what, you know, some of these things related to clinical.
Jón Bergsteinsson: Thanks, Etienne. Always a pleasure.
Uh, well, I've been doing this for a little bit more than a decade now. Started out in the industry back in, what was it, 2008 or 2009, working at a clinical trial site.
Got firsthand experience of, well, all the pros and cons of collecting data from patients from physicians out there in the real life.
Fast forward to 2013. I founded Smart Trial now by Greenlight Guru. We're together with my colleague and for the last 10 years I've been dedicating my career in helping medical device and med tech companies in general collecting clinical evidence out there in the well, out there in real life from patients, from physicians, from distributors, from anybody that might have anything to do with devices safety or clinical performance out there in the field.
So, for the past couple of years, I've dedicated a lot of my time sharing that experience and insights with the rest of the industry. So, I'm also very active online and LinkedIn and conferences and speaking.
So glad to be here once again, Etienne, on the podcast to share some of that experience with you as well.
Etienne Nichols: Yeah, and that's one of the things I wanted to bring up too…
As he already mentioned, he's very active on LinkedIn and I highly recommend you go follow him if you're active at all on LinkedIn and interested in clinical or anything related to EMDR or any of the, you know, there just anything related to MedTech.
He seems to have a wealth of knowledge, so definitely follow him on LinkedIn. If you get a chance to get over there, we'll put a link in the show notes as well. So, it'll be easier to find him.
So, you see a lot of things. You're, you're kind of on the cutting edge. So not only have you worked with companies, because a lot of times that's a good indicator, but you're also at conferences working with other people who are working with companies going get through their clinical trials and clinical investigations.
So, one of the things that I'm always curious about is being on the cutting edge. What are some of the biggest challenges you see companies facing during their clinical investigations?
Jón Bergsteinsson: That is a big question because it very much depends on A where you are located as a company and B in terms of like geographical location and which regulatory framework you're following or, and B in which stage you are as an organization.
But I'd say it comes in trends like now very much. For the past five years or so, people are caught up in the EU MDR, not only here in Europe, but also in other side of the Atlantic, North America, South America, and medical device manufacturers from Asia.
They were trying to figure out how can we continue with selling our products in the European market? Because the European market is the second biggest MedTech market in the world.
A lot of devices have been put to market there under the MDD, the Medical Device Directive.
So, a big portion of the conversations and the challenges that I see people talk about is regarding the EU MDR.
However, there are still, I hate to say it, but still 10 years into the industry, from a vendor's perspective, supporting clinical operations, there are still way too many companies talking about the same issues over and over again regarding clinical investigations. That's, how do I make sure that the quality of my data is sufficient?
And it really is funny thing to mention that it actually also correlates highly with the EU MDR.
But the same question tends to come up, like every time I go to conference, whether it's one or two speakers, how do I make sure that the quality of my data is sufficient when either A presenting to the FDA,
B sharing it with my sales reps and then presenting it to a potential buyer or D and making sure that, for example, notified bodies on the European side of things considered it, you know, appropriate for my CE mark.
And when it comes down to it, people try often link data quality, clinical data quality with good clinical practice, because good clinical practice is a guidance that has been generated for the clinical research industry to, you know, make sure that you're following ethical principles and, you know, ensuring, ensuring certain amount of documentation and processes to make sure the data is of adequate quality.
And we have a standard for good clinical practice in the medical device industry.
But when it comes down to how can you demonstrate that a data or data produced in a clinical trial or clinical investigation for a medical device is of sufficient quality or not, people tend to take that up as their excuse.
Like this is how I demonstrate quality. I follow the standard. You know, I don't know. Have you, have you seen that standard? I don't know how much you know about that standard.
Etienne Nichols: Which standard are we. So, I've seen ISO 4155, but.
Jón Bergsteinsson: Yeah, yeah, yeah, exactly. ISO 1 form 155. So that standard has a ton of sections like any other ISO standard that cover broad, you know, topics such as, you know, investigational brochure, what is supposed to be contained within that.
And for example, when you're planning your clinical investigation, what is supposed to be tained in your plan?
So, when you really look at the standard, it has a lot to do with the processes around clinical trial.
But when you really dig into the standard, it doesn't have anything to do with the data quality itself. Like when you think of data, I'm, I'm talking about like the quality of quantitative or qualitative data that, that is then produced, used to produce reports or graphs or outcomes.
Like there's like a section or two that focuses on tools that you use for data capture, if at all during your study. How, what should that entail?
So, and when it.
Etienne Nichols: Yeah, sorry, didn't mean to interrupt but I just, it. You made me think of something. So, when you're talking about the quality,
I just, to my, my, my lateral thinking is kind of going a different direction a little bit. So, when I think of, I'm just going to use a different example outside MedTech.
So, a lot of times when we're writing something, we, we want to get our content across, we want to get our, our.
Sometimes we forget about the formatting, so it doesn't actually get read. And I wonder if that's almost a little bit, I mean that's, that's a dumb, dumbed down example, but that seems to be one of the things. You got your content, but you also have your formatting, so it actually is digested.
Jón Bergsteinsson: Is that a. Yeah, that's correct.
That's probably a good way to put it because data quality has everything to do with how you format your data, not only in terms of when you're presenting it to somebody, but also in terms of how you collect it, how you frame your questions, how, how you standardize the questions that you can asking in the clinical investigation.
So, when I am at a conference and I hear somebody talk about how to ensure high data quality, how to ensure sufficient data quality, how to ensure sufficient clinical evidence, it always bugs me a little bit because they're talking about the, the processes around a clinical study, not the data quality itself.
The data quality is so important.
How you format it, how you frame it, and how you are able to produce graphs and tables that you use then to tell your story to the FDA or tell the story to another body.
It's so important because when it really comes down to it, there are way too many publications out there or research papers out there that have missing data or scattered data or illy formatted data that has resulted in them using statistical methods to compensate for that.
It's actually very common to compensate for missing data by using specific statistical methods which then can try to help you guess.
If you had 200 samples or 200 patients that all gave a fully, you know, compliant answer to your question, how would that have resulted in, how would that result have looked like?
So, when somebody is talking about medical devices and clinical investigations, it is still a huge, huge challenge for a lot of companies to make sure that they're collecting high quality data.
And a lot of it has to do with effects that the tools that they've been provided, whether it's acquired or whether they're just following the flow of how everything has been done in the past, has a lot more effect on the data quality than anything else. And here I'm talking about, for example, paper, Excel, other outdated tools, they still have a huge influence on the data quality in our industry.
And a lot of the times when I meet professionals in the industry that have been doing this for years, they tend to tell me that, well, the reason why we're still using, for example, paper for clinical investigations is due to cost.
Like it's pure cost reasons. I know that it's better to do like digital first and it's more efficient, but you know, the MedTech industry, we just aren't presented with the same cost-efficient solutions as pharma are because truth be told, pharma budgets are just a lot, lot bigger.
Etienne Nichols: And that's interesting that you bring up the tools because so in my side of the world, I guess when I think about design controls, which is where I prefer to live my life, because it's just what I'm comfortable with being product development background.
So, when I think about design controls, same issue really. I've seen people use Excel, we could Talk about the benefits or downsides of doing that. If you have only one person in that Excel file, maybe it's going to be stay, stay what it should be.
The more people you get. It's almost an exponential risk factor.
It's not just one plus one is two, it's one plus one is now three as far as your risk factor. So that being said, so I just basically saying that say I can definitely identify from that perspective, but you made me think of something.
So, when you talk about the different tools.
We just conducted a benchmark study for the state of MedTech for 2023. So, I'll put a link in the show notes to that study. But based on that industry report and just a little bit of background, it was 613 MedTech professionals that were interviewed.
Whether it's quality product development, mostly quality, I believe quality and clinical regulatory.
44% of those companies we heard from are still using general purpose tools such as like you mentioned paper, Excel, Word.
So, if we were to use a tool that was designed specifically for the industry, what kind of impact do you, do you and would you anticipate a company experiencing? What kind of impact would a purpose-built tool have on that company?
Jón Bergsteinsson: Well, I have, I have that conversation almost daily because there are still way too many companies that approach us to exactly get that questions answered because I don't think it's that clear for the industry from the outside.
Because when you look at it, when you start digging into the concept of clinical investigations and data collection, the tools that you use is usually not the first thing that pops up.
What pops up is the guidelines and the standards and the requirements that you need to have and so forth.
So, when you start weighing out the pros and cons of for example, should I use paper or Excel or Word like I've done throughout the years of like my friends or colleagues have done, or should I go with electronic data capture or electronic clinic case report forms?
The question usually tends to come down to cost. Always.
It's just a fact. In the MedTech industry is very much driven by costs.
And that's where people tend to be biased a bit. Because when you are looking at up to buying a solution for a clinical investigation that you're planning or for your clinical operations overall, you see a price tag and then you think okay, that is like X amount of dollars.
But my Excel or my paper is only zero or maybe marginal $10 or something because of printing costs.
Why would I ever, you know, pay X while I can do paper and Excel or work for free Makes a lot of sense. Right, but that's where you need to start looking to the other factors outside of the like cost of implement, cost of, of acquisition, the cost of operation, the cost of compliance, the cost of data management as it's sometimes called, the cost of training and traceability and the cost of reduction in data errors.
That's usually costs that can be very, very difficult to demonstrate for a new organization.
So, what people tend to do is that we take examples from others that have done something similar in the past and luckily now we have a couple of publications that are actually almost.
One of them is around 10 years old, another one is 10, 12 or 15.
And then there are also some newer publications too where somebody has taken the time to actually research this.
And every single one of these publications that I've looked at, they've come to the same results that time wise overall, and in terms of overall data quality and execution and relief and control and overview that you have of using a digital tool for data collection and clinical investigations for medical devices or medicines is much, much more cost effective than using paper or Excel.
Not to mention the fact that you can't really use Excel or any other off the shelf solutions anymore because of validation requirements.
Etienne Nichols: Yeah, and we probably ought to touch on that a little bit more in just a second, but you made me think of a story. So, I don't know exactly when SolidWorks came out, but I worked at a company once where they actually had, they, they actually had hand drawn drawings. And I'm moving towards; I'm using an example from my product development background.
So, we had hand drawn drawings, we had microfilm, we had SolidWorks, AutoCAD, we had. What else was there? NX Ideas. There were five different ways to pull a drawing.
But think about at one point they were using hand drawings on a drafting board. At some point all of the people coming into the industry were used to a 3D modeling software.
And, and we expected SolidWorks or Solid Edge or CREO or something, you know, so that we could do this.
And so, I bring that up to say I mentioned 44% of the companies are still using things like Excel Word. And you already mentioned some of the issues from a regulatory standpoint with using those.
But okay, let's say 44% are using that. That means 54% are using some other kind of tool, whether it's specific to MedTech or not. It is, it seems to be electronic data capture, some, some sort of tool.
Does that mean kind of like my example from SolidWorks, does that mean, people coming to the industry are going to start expecting this from a clinical and it's actually going to be a competitive advantage to be using one of these electronic data capture tools.
Or, or is that too much to think? What, what do you think the future looks like as far as that goes?
Jón Bergsteinsson: Oh no, yeah. I can tell you one thing.
The professionals that I meet that are introduced to a new organization where there's a completely different budget, maybe it's a startup that has acquired a Series A or Series B and they're still trying to get the product to market.
Or they might not have any clinical studies conducted to date. If, if so, there might be some early-stage feasibility or first in human.
When these professionals come into the organizations and they hear that they only have paper, they, they tend to go, well, sour a bit. Because when you're getting used to something that's effective and you know, and you could tell maybe from your previous experiences working in another organization that is just much more cost effective, but it also relieves the compliance that you need to take care of when it comes to good clinical practices.
Going back to square one is like, you know, well, yeah, it's frustrating.
So, you're right. If you want to keep good talent, if you want to make sure that you continue to streamline and become more effective, you need to make sure that the people you're hiring get access to the right tools.
I have had multiple conversations with people that are evaluating our solution for the clinical data capture.
They're coming from a large organization like I'm talking, you know, organization like Top 10, MedTech, Philips, you know, Medtronic, those kinds of organizations, they're used to doing stuff in a very, very high-quality manner. They maybe have access to all those tools from pharma to, and then they get into this medium size medic company that's been doing paper, QMS, paper, clinical data collection and they're just like we need to; we need to shake things up here.
And they tell me that they don't have the budget to do it.
And that's usually where we help them build up the business case. Because sometimes it's just a matter of education.
Yeah, you know, the leadership just doesn't have that much of an understanding of what clinical operations do. So, they need to be educated and that's where you need to arm people with the materials that are available out there, the publications, the business cases that they can understand.
Not only is this more cost effective, but you, it actually provides your people with a certain sense of control, oversight, calmness, to conducting the clinical study.
Etienne Nichols: When, when you talk about that, that clinical affairs, a lot of people don't know what the clinical operations occur outside of, you know, their organization. I would be guilty of that.
In my, in my experience in medical device companies, I remember it almost being like just a, a fuzzy haze once we send our, I remember getting ready for an animal trial and it was a, it was actually a little bit of a nightmare because it was something new to me and we just assumed regulatory, did all of the, all of the paperwork and all that stuff.
But no, there was a, there was a little bit of back and forth.
So, I'm curious that you mentioned the education.
You know, can you give us some of that education or can you, you know, even I can give a link to business cases like you mentioned.
Some of those, some of those aspects.
Um, yeah, to, to help build that business case.
Jón Bergsteinsson: Okay, so there are a couple of. So, if you're planning a clinical investigation for a pre-market approval of some sort, there are a couple of options when it comes to the data capture itself.
Um, most of the time it's just a matter of finding an applicable case report form tool or a questionnaire tool that, you know, ECRFE Pro, sometimes called as well, EDC.
And then you have a range of vendors out there in the industry that might have been working with pharma for years. And then you have vendors like ours where we have been working with the medic industry for 10 years.
And when it really comes down to it, you need to look at what is it that makes me most successful. And if you're talking to a meta company, you need to, you need to look at a couple of different things.
For example, okay, how big is my team and how many activities are we planning?
If you have a small team and you don't have a lot of activities, you know, settling for a small, you know, small package of some sort that can at least provide you with the minimal functionality needed to collect the data in the study is usually sufficient.
Getting the people trained to manage it themselves is usually preferred because then you don't have to produce, you know, additional resources to manage the CRO necessarily or a consultant.
However, many companies tend to choose to include a CRO or a partner too.
So that's kind of like, you know, one of the two options that you have.
The second option you need to validate is how do I make sure that I can streamline my compliance part of things. So, you, for example, need to make sure that you comply with ISO 14145 and there are number of sections in that standard that, that cover data collection.
If you're going to do it on paper, you will have a hard time documenting that using a platform that is already compliant with the ISO 14155, you relieve a lot of that pain.
So, there are a couple of aspects to what can go like aspects that play into the role of, you know, the business case itself. But most of the time it's about reducing efforts, okay, for example, reducing the time it takes to set up a study in ACE platform.
That's one, one big factor. Reducing the time, it takes to get a subject enrolled, collect data around that subject and for example, closing out that subject. Because, you know, clinical studies are always about patients. So, and every single patient needs to be treated in the same pathway.
And just making sure that every single case is like covered, we have all the data, no other things need to be done like that is important.
That can take a lot of time, not only from your side, but also from the clinical side. So, you need to make sure that you have a system that allows that to be done like in an efficient manner.
Three, there's what's called a study closeout time, which is also tends to take, you know, everywhere between three to nine or 12 months for some systems to complete because the vendor needs to be involved and you know that IT staff member needs to be contacted too.
And you know, a certain number of people need to be included in that. So that can take a lot of time. So, you need to make sure that these time efforts that are put in place can be reduced by selecting a vendor that takes care of those, either by simplifying those processes or giving you the power to do most of the work.
And then you have the cost factors related, for example, to reduction in errors and data quality in general.
So, this is where you, for example, have to start looking into things like, okay, if we're having, you know, a small 15 or 20 subject study, how do we make sure that out of these 300 attributes we're collecting on each subject, we get every single one of them into the system correctly.
Okay? And that's where you have to look at a system where, for example, allows you to create simple rules and checks very efficiently so that you can enable and guide the user in entering data.
Because on paper, you can't do that on paper, you'll end up having a stack of paper. And then when somebody finally gets the time to go through each and every paper to transcribe it into the system,
they start funding errors and they starting, you know, checking off things and then they have to ship it back. You know, it's just a whirlwind of time-consuming work added on top of everything.
And then of course, it's the compliance part too, which is also can be very costly if not done wrong. So, if you get an on-site audit, does your platform simplify access to the, you know, study database so that an auditor can review it?
Does your platform comply, the Nest comply with the necessary requirements of the ISO?
Do they provide the documentations and the materials that are provided together with the platform in an efficient manner so that you don't have to waste a day or two in auditing on finding those materials?
And when it comes down to it, the RI for every single organization is very different.
And it's even much, much, much bigger for those that have been doing paper and then switch over to an EDC or an ECRF or E Pro versus those that have never done a study before and then launch the first study with a digital solution.
Of course there's no like, comparisons been made there, but if they would have done paper and digital study at the same time, you would see an ROI that would be, you know, interesting to.
Yeah, from a leadership perspective.
Etienne Nichols: Some of those things are hard to quantify too, because just like we mentioned, just satisfaction of your employees or the frustration that people are going to feel having to use this tool.
I'm curious, you know, you work with a lot of companies, you go to a lot of conferences.
I'm curious if you have any specific stories that you could share about this, because when you started talking about all the 300 different attributes that you have to manually enter, I'm picturing, okay, somebody gets tired of writing, can you even read their writing at some point?
And then you have to manually upload that into Excel or wherever it is to, to crunch the data.
Do you have any stories about that?
Jón Bergsteinsson: Yeah, probably the most memorable is the one I have from a country I visited back in 2019. Probably I was, I was going traveling to this country almost every month, visiting a number of prospects and customers at the time.
And one of the companies that I met with was a medical device company that had been doing studies in Japan.
And I met with a VP of Clinical Affairs.
Guy has been doing clinical operations for MedTech for years. VP, different companies. He knows, he knows his stuff.
And we were just, you know, contemplating on how we could potentially support their upcoming study. And then he said, well, well, let me show you something. And then we walked into the room beside of his office he was like, hey, check this out.
This is the DHL box we got from Japan last week.
I'm like, okay, what, what is that? They were like stacks of 10 boxes. I mean, I don't know what measurements you would, I would use in, in the U.S. but they were like 50 centimeters times 50, you know, probably three or four rows of paper stacked on top of each other. And they're like 10, 10 boxes of that.
And he was like, yeah, those are our CRFs case support forms.
And I was like, okay, are there, is that archiving or. No, no, no. We, we haven't analyzed the data from the study yet. We're looking to do that hopefully very soon. I'm hiring a person to do it.
And I was just like, oh my God, this is the biggest real use case I've ever seen in the MedTech industry today.
I was stunned.
You know, I tried it myself. I'd worked at a site completing these paper forms and then transcribing them partially. And I, that was like for 30 patients or something like that.
And it was a fairly small study, but that study was like a year or two follow up study with a lot of different attributes on each and every patient. And you could just imagine the amount of work that had to be done afterwards.
Yeah.
Etienne Nichols: How much, how many, how much time do you think it would take to input all of that data? I mean that's probably hard to quantify, but did they say how much time they spent doing that?
Jón Bergsteinsson: Funny you should ask because we did do something like that years ago.
Um, and we, we recorded the time. I think something like we, when you have a person that's very efficient, you can get like 100 attributes in, in a couple of minutes.
So, I mean probably a patient would take an hour or two, you know, so it would probably take like a week or two of continuous work if you're going through like 50, 60, 70, 80 patients.
And that is only if you totally understand everything to the point there are no writings you need to decrypt or if there's no missing data or no misleading answers like crosses in two boxes where there's only supposed to be one X.
When there's nothing like that. You could do be very efficient.
So, you can imagine all the additional work on top of that that would need to be included if you were to, you know, to figure out what, why there's missing data.
Etienne Nichols: Yeah, quality data. That's the, that's the key. So, I guess one last question I have. So having seen all these, are there any, any things that you've seen that really set the best of the best apart from the rest. Are there, is there anything like that, that, that that stands up when, when we start talking about this quality data?
Jón Bergsteinsson: Probably starting to sound like an old record, but digital first is what sets the best from the, yeah, from the rest. Because I can, I, throughout my career in this industry for the past 10 years now, I can tell that the, the companies that put a lot of focus on clinical research are the ones that are really, really, really in the top and the ones that are focusing clinical research with support of smart tools.
So, more work for less, they do tend to do a lot better.
And I think that it's just, it's like the industrial revolution. I mean those that have the machines can produce more and it's just the same with clinical research and clinical operations in MedTech.
Those that have the right tools will be able to do more, generate better evidence, produce better medical devices, help more people.
Etienne Nichols: Yeah, I think that's well said. And if the point is lost, I really, I, if, if we were having this conversation to engineers about their 3D modeling tools like SolidWorks, they'd be laughing at us. You know, this would be like, of course this is a no brainer.
Who uses a drafting board still, you know, hey, we got by on drafting boards for years. Why would we switch? Oh, you know, that's just like why would you even have that conversation? And I think at some point it's going to be similar with, with this kind of tool when you're, when you're talking about cross facilities.
Jón Bergsteinsson: But yeah, I also think it has a lot to do with the fact that the regulations and the regulatory environment in MedTech has just not been focusing enough on clinical evidence. In terms of, when I say not focusing enough, I'm talking about not requiring companies to collect as much data because of that fewer companies have been doing so and more. Those that have been doing so have been getting by with doing simple ease, not simple, but spending less money on it, less resources. Just let's try to get by.
Whereas now in Europe you have to collect data, and you have to do it in an efficient manner with high quality.
Etienne Nichols: Yeah, well, this is good. Anything that you'd like to, anything you'd like to add or as we kind of wrap up here.
Jón Bergsteinsson: Well, I know that we've been producing some material on our website recently on the topic of, you know, paper versus digital tools and the comparison between those.
So, I would encourage every. Anybody that has, you know, is weighing out the pros and cons of these to check it out. We have some good facts and resources in those contents and blog posts that you know tell the story better than we would ever do.
Etienne Nichols: Cool. And where can people come to find you to learn more? Do you mind if they reach out.
Jón Bergsteinsson: To you or yeah, of course. LinkedIn is my favorite spot, so just hit me up on LinkedIn. John Berk Stinson Always up for a chat if needed.
Etienne Nichols: Awesome. Okay, so in the in the show notes, I'll be sure to link to our paper versus Digital comparison, the link to the benchmark study that I had mentioned, and of course link to Yon's LinkedIn so that you can find him and reach out to him directly.
Yon, I really appreciate you taking the time to be on the podcast and yeah, looking forward to seeing you again in person one of these days.
Jón Bergsteinsson: Thanks, Etienne. Likewise. Have a good one.
Etienne Nichols: All right, take care. Thanks for tuning in to the Global Medical Device Podcast. If you found value in today's conversation, please take a moment to rate, review and subscribe on your favorite podcast platform.
If you've got thoughts or questions, we'd love to hear from you. Email us at podcast@greenlight.guru.
Stay connected. For more insights into the future of MedTech innovation and if you're ready to take your product development to the next level, Visit us at www.greenlight.guru until next time, keep innovating and improving the quality of life.
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