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Good morning, everyone. Welcome to the fourth session um of the research in the NHS teaching series. Can everybody see and uh hear me clearly, please? Yeah, just check if my microphone is working. Yeah, so we've got a good microphone going on. OK. Yeah. So in this session, we'll talk about clinical trials and how clinical trials are conducted. And um um because clinical trials is again a very a long um it has a lot of uh complex concepts to how clinical trials are conducted and there are so many different uh types of clinical trials that are, that can also be conducted. I'm gonna try and stick to the basics of clinical trials and what you need to know um when you join a team of um clinicians or a team of researchers who are going to be doing a clinical trials. And uh if at any point in the session, if you have any questions, feel free to um put them down in the comments section or in the chat box. And um we'll go through it at the end. So just some basic housekeeping rules that we're all aware of and a bit of a disclaimer as well. So any opinions, um or any experience that we share related to anything in the NHS is purely, um our own opinions. It doesn't follow any guidelines. Um, nor does it follow anything that our trust also teaches us. So this is just, um, us trying to give you some free advice, um and just sharing our experiences of how research can be done in the NHS, easily as a junior doctor or as a junior level. So just a bit of a disclaimer out there for all of you. So what is a clinical trial? So this is a topic, I think a lot of us must have heard because it comes up in a lot of newspapers and magazines, you know, clinical trials are going on for this particular drug or clinical trials have gone wrong. A lot of side effects have come out but trial is the bread and butter of us doctors giving out medications to our patients because if we don't know what different treatment options there are for a particular disease, we might not be able to give our patients the right choices to make for them. So any medications that are available in our guidelines, um, in our protocols are all the main theme behind it or the main reason for it is the clinical trials that have gone on and tried and tested different medications to see which works best for patients and the way clinical trials are done nowadays, I think it's, it's much more complex. It's a much, it's much more accurate. Um And it's ii would say it's much more robust as well compared to maybe how clinical trials were conducted a decade or two decade, two decades ago. Because now we have a lot of procedures, a lot of stages to um follow and tick box at every point. A clinical trial is nothing but basically it is the gold standard of finding out if a particular drug or a treatment is effective for that particular disease. So what I basically do in a clinical trial is if I was a researcher, I would get a group of patients volunteers and I will just randomize them to two different groups. And I will give one group, the drug that I think is quite good and is effective. And I'm going to give the other group nothing which is called a placebo. So the placebo could be just like an empty tablet. Um If it's not a tablet, it could be just some cell line like an injection. So that will be like a non-effective form of medication. And then I'm going to see if I can um see any difference. Now, if I can see any difference, it depends upon the outcome that I'm trying to measure. So for example, if my outcome is has the pain reduced, if I'm trying to find out the effectiveness of a painkiller, do you do? I think that the pain has reduced the pain. So, is my outcome a pain relief or is my outcome? Maybe weight loss, maybe this drug has resulted in a weight loss of that patient. So this is a very good medication for weight loss patients or it could be, if I'm doing surgery, my outcome might be have I reduced the surgery time or have I reduced the amount of blood loss in the surgery? So, depending upon what you're trying to find out and your, what your intervention or what your treatment is, your outcome will be different. Now, this is the only um research as researchers where this is the RCT S is the only type of uh study design where we intervene and we give something to the patient and then we test it. Whereas if you look at maybe like a case report or a cohort study or a cross sectional study, we are just observing as researchers, we observe and we see if there's any changes in the uh in the progression of the disease, if there's any risk factors. But RCT S are the gold standards because we, as clinicians, we intervene into the patient's medications, into the patient's treatment and we try to see if there's any difference. Um And if we can make any difference in their treatments and in the diseases. So that's basically the overall idea of how uh R CT is done. Now, why are RCT S so uh promoted and why have they become um you know, the best type of er study design there is. Well, this is I'm gonna bring back to the triangle, the body of evidences. So these are all the different types of study designs that are out there for us to follow. And as you can see, they are the gold standard because they are right at the top of the pyramid just below the systematic analysis and uh sorry systematic review and the meta analysis, clinical trials are just right at the top because the reason for this is the way the pyramid is sort of um designed. As you can see, as you go up the pyramid, you can find, you can see that your study is much more valued. So if I were to do a case series and if I were to do a systematic review, the systematic review will have higher value that will be, that will be more, you know, more chances of it to end up on your um treatment. It can change the way we treat. The reason for that is as you go up this pyramid, the level of bias, the amount of bias reduces. And that's why it has been sort of put into a pyramid. As you travel up the pyramid, the amount of research bias reduces. And RCT S they are the gold standards, like I said, because we basically reduce or we make sure that we don't have any research bias. We try to have any research bias in any way. So we're making sure we're completely testing whether if that treatment is effective or not. And we do that by making sure that there is literally no bias at all. And the way we do that is what I'm going to be explaining in the upcoming session in the upcoming slides. Now, how do I do a clinical trial? So you always have to remember as when you compare to uh maybe like a, like a cohort study or a cross sectional study, other types of studies, they're all, it's very easy to do them alone. You know, if I've got, if I've got myself and maybe I've got a colleague, we can sit together, we can make up a paper, we can write up a paper and get it published. Whereas RCT S are always done in groups or in the, it's a team as much as we think that, you know, working alone is much more effective. It's easy to get the work done. You always have to remember that when it comes to things like RCT clinical trials, it's really important to work as a team because we need the input of every member. We need every single one of them to be a factor because it includes, it involves a lot of different types of um stages. It involves a lot of screening, it involves a lot of monitoring. So you do want to have AAA good amount of people in your hands to make sure that they are able to do each step effectively. So the way we start off with a clinical trial is to have a research question. So what is it that I'm trying to find out? What do I think is a better treatment? Um, in terms of what's already I'm giving? For example, do I think that this medication, this medication a is better than what's already been given to all the patients in my hospital? So I come up with a research question, then what I do is I try to recruit patients and I try to see if I've got a new medication and I think that it, it works much better. I'm gonna recruit the patients and I'm going to try and give these medications to them. Now, before you recruit, you have to obviously write out what you are going to be doing what your treatment is. I mean, what your aim is, what your objective is, uh, how are you going to select your patients? Um, and along with how are you going to give the medications, how long are you going to wait to see your outcome? What is the outcome you're trying to measure and, uh, what are the, uh, ethical aspects of it? So all of this will be added into a study protocol. That's, it's a, basically a write up like a draft of your research plan. You write that up you select your group of participants, the patients, you obtain consent from them after explaining to them thoroughly what you're going to do what you will be giving when you will be giving, what sort of um side effects you're expecting if you are expecting any and what are the risks they might be involved in it now? And there's a lot of way to actually get patients um to come into your clinical trial. So there are, you know, um ways where you can also recruit them. For example, you can advertise it in a newspaper saying that we want a group of healthy men or healthy women and we want them to participate now again, because, you know, it's very hard to get participants to come and be committed to your clinical trial because we're all busy with our lives. So a lot of clinical trials, what they do is they obviously have some kind of reward. So if you participate, maybe you will get this as a reward. So I think in 90% of the time, it's obviously monetary. So there will be some kind of money involved behind recruiting participants. Um This is quite interesting because recently um in the UK, there's an ongoing um it's not a clinical trial, it's a research study that's going on and it's Pan UK, that means it's a national level. Um It's done throughout the entire UK. And what they're trying to do is they're trying to recruit as many people as they can into this study from different origins. So, from Asia, from Africa, um Hispanics, Latins, uh Americans, and what they want to do is they want to get us and get some of our blood and study our genes to see if we are at any particular risk of developing any kind of diseases in the future. So this is basically trying to look at the risks of a particular um ethnicity, developing a particular disease in the future. It's a huge trial and obviously there's gonna be a lot of um funding involved in it as well. Now, when you have a huge trial and you want a huge participant, you obviously need to have some kind of monitoring um reward to it. So, and it was very interesting because this came through the post. Yes. Um the other day uh in my house, they basically sent out as many letters as possible to different people, different addresses in the UK. And they've asked them please to visit their local GP um you know, to get their heights and weights measured uh to give some blood. And if we do all of this, we basically end up getting 10 lbs voucher um to spend at a supermarket. So this was um quite interesting. So this is a way of um recruiting patients to take part in your study. Then once you've got the consent, then you obviously intervene, you give the medication and or you don't give the medication, you put them in the placebo and then you collect data, you, you observe what they do, what, what's happening to them. You see if there's any change, what, whatever you're trying to uh measure. And once you've got that this will probably go on for months and months. And once you've got that, then you start obviously plotting it into graphs or in uh bar charts and you try to see if you have uh you know, come out with any um significant outcome in your research. So this is the overall stat. And as you can see this RCT S can go on for years sometimes. And it involves a lot of funding, a lot of effort, a lot of manpower as well to make sure the clinical trials are conducted and lots and lots of tick boxes to be ticked at every step. So quite a uh a bit of a long tedious process, but that's why it's so much valued because the outcome that you get from this can completely change the way we treat patients as doctors. Now, the first step that I wanna talk about a little bit and this was also covered in the previous session as well. The first question or the, the F I think the way to do a clinical trial is to start off with having the right question. Now, the way we can have the right question is only if we know what's wrong or what's happening. That might be that, that you can improve in your clinical setting. So only if you practice, only if you practice years of years and years of practice treating patients, giving out medications, prescribing medications, looking at side effects, you'll be able to find out what's wrong with it. So getting the right question right comes from your years of clinical experience and when you've got the right question in front of you, you always want to put in this po framework because this po framework, I think if you've got all of it, uh almost uh all of it, you will have the perfect question to it. An example of AP O framework that I have recently found out found was if I wanted to find out um if I do maybe a cholecystectomy or wait until the patient becomes progresses and then do an delayed cholecystectomy in a patient who's got c acute cholecystitis. Will there be any kind of difference? And the way I do that is again, I go back to the P I see if I've got the population right. Yep, acute cholecystectomy patient. And am I going to do some intervention? Yeah. As soon as I diagnose them with cholecystectomy, I'm gonna take them up to the surgery, remove the uh gallbladder or am I gonna wait until I hit all the criteria for the surgery and then take them up to remove the gallbladder? So that's my, that's my control. And what am I trying to find out? What is it that, why am I getting their gallbladders removed? I'm trying to find out if I, if I can reduce the complication of cholecystitis, which is CBD injury rates. So that's the, um, outcome that I'm trying to measure. Now, a lot of studies do start off with not having the timing because like I said, it's very hard to, um, say within this particular time frame. I'm going to expect 100s or 203 100 patients. I'm gonna do so. Some, some uh researchers take time to pick up some research are quite easy to do. So timing may or may not always be uh ideal thing to put at the beginning. But it's, it's important to have at least an approximate time where you think I'll do this for this uh particular time and then see how, what the outcome is and setting as well. So setting obviously or most of the time happens in a hospital, which is called the Pragmatic. Again, we check, we talked about this in the previous er um session as well. So in a pragmatic trial, we do this in a hospital and we see if there's any effectiveness. Whereas if I say no, I think I'm gonna do this clinical trial in a lab in a research clinic, then I will do explanatory because I will put the patient in ac in a lab and I'm going to control everything and I'm going to monitor them 24 7 to see if I've got any changes in their outcome. So always having the pi of framework in in your mind, when you're thinking of the right question or thinking of a clinical question is very important. So next, once I've got my question, now, I need some people to experiment on them. So how am I going to recruit? So asking for a couple of people to come in, take part in my study? Yeah, that's fine. But there has to be some kind of criteria for them to be suitable to participate in my study. Why do I do that? Why can't I just record everyone and every everyone that I see. Well, how you recruit actually has a huge difference in how you the validity of your clinical trial and the way we recruit is we screen the patients by having some inclusion criteria, that means everybody has this. I'm going to include them in the trial and people who have this, I'm going to exclude them from the trial. So that's an exclusion criteria. So what do I mean by an inclusion and exclusion criteria? So an inclusion criteria, like I said, if they're going to have da da da da, uh they will be in my study. Now, having an inclusion criteria is again, it has to be very clear, it has to be quite accurate about what you mean. An example of an in an inclusion criteria. I've given two examples, good and bad. So let's look at the bad example. So I said subjects who will be included will be people who have insomnia. So if I'm trying to uh do a clinical trial on a medication which is going to help with insomnia, and I say everybody who has insomnia come take part in my study, that's a bad type of inclusion criteria because what is insomnia? Is it like insomnia that you've had last week or you had insomnia a year ago, a decade ago? When do you want them to have it for you to choose them? Whereas if I say I'm going to include subjects who have been diagnosed with insomnia and they've had symptoms for at least three nights a week in the past three months. Minimum. Now here my diagnosis, my criteria is very clear. I know exactly what kind of patients I want in my, what kind of subjects I want in my study. And this is very easy for someone who's recruiting also to, you know, quickly gather up all the patients who might be suitable for your criteria. So having a clear cut inclusion criteria is very important because that really tests your validity of your clinical trial. Now, exclusion criteria again, if I'm going to say I'm not going to have these, these, these patients, for example, subjects who would that will be excluded are those who take medications? Well, what kind of medications. I think almost all of us have taken medications at some point. It could be a painkiller or it could be womens who are on, you know, women who are on birth control. What kind of medications are you talking about? Whereas if I say subjects that will be excluded if they're currently on any medication that's affecting the sleep or prescription drugs or anything that the, in the opinion of a researcher that may interfere with the results of the study. Now, so here I'm having a very clear cut idea about what kind of medications I want. So it's very important to have a clear inclusion and a clear exclusion criteria. And also whenever you're reading a paper as um when you, you know, when you're in your initial stages of doing research and you're reading, gathering lots of papers about clinical trials, don't read the abstract and think, oh, this is a good paper. I'm gonna take it because abstracts will never have inclusions and exclusion criterias at all. So always try to dig into the paper, look at the inclusion criteria, see if they've included the right kind of patients for the particular trial and then try to test if you think this research might be robust or it's a quite powerful research or not. Once I've got the patients after screening them through the different criterias, what I'm gonna do is I'm going to randomize them. Now, this is a very popular term, a popular concept that's used in clinical trials. And remember how I said that clinical trials are right at the top because we reduced the bias because clinical trials are very powerful because what we do is we randomize the patient and we reduce the bias. So what do I mean by randomize is basically me trying to put different patients in two different types of groups. So a group of patients will get the treatment, group of patients will not get the treatment. They will act as placebo. The way I do that is I randomly allocate them to different groups. Now, why should they randomly allocate them? Because if I'm the researcher, if I'm the one who's come up with the ideas I've put in the uh so much effort, I've got the group of pa participants in front of me and I'm looking through it and I think, and I, and I think, oh, all these healthy men are going to, I think I'm gonna give them the treatment because I think they're going to come out with a good outcome. That's my research bias coming into them. I'm looking at the participants and I'm thinking, oh, these, these guys probably have a very negative prognosis. They don't have risks at all. I think they're going to give me a good outcome. So I'm being very biased here. Whereas if I don't get to look at the participants and I just randomly, you know, put them a by chance in different groups. I'm making sure my opinion, my bias is not at all interfering with the treatment or with the research that's going on. Now, randomization can literally be done by anyone and the more you randomize the better. So it could be done by a doctor, it could be done by even uh research nurses, it could be even done by a company from outside uh an external company. And nowadays, there are software programs available where they can easily just randomized people um randomly. And there are again, different types of randomization as well. You've got the simple randomization just, you know, simply allocate them whereas you've got stratified. So here, what I do is I think I say because the study is focused more on female, middle aged female. I think I'm going to try and give middle aged female um more in the treatment. I'm going to keep, give them less in the control treatment. So stratified randomization can also happen and then block randomization is also another option. So randomly allocating them to reduce the bias, making your clinical trial more powerful. Once I've randomized them, I'm going to give them. Now, I'm going to intervene as a researcher, I'm going to go in and I'm going to give them the treatment. Now again, I'm going to give another checkpoint a checkmate to my bias because what I'm doing now is for example, if I'm a surgeon and I'm trying to do a clinical trial. And I, and what my clinical trial is basically is if I've got patients with knee osteoarthritis, I'm gonna take them up to surgery and I'm going to fix them and I'm going to see if they work out better versus, um, taking them, giving them painkillers, not having any surgery, just giving them some painkillers and see if there's any difference in their pain relief. So, if I'm a surgeon and you give me a group of patients and if I know these guys have osteoarthritis, I'm gonna take them into my, uh, theater and I'm gonna do the best I can to make sure I, uh, I do a perfect surgery. I get rid of all the debris in their cartilage. I perform really well. Whereas if I know of this patient doesn't have osteoarthritis, he's just a control, I'm just gonna do a little bit of, you know, surgery because I know he doesn't have, he's not gonna contribute much. So, here as a surgeon, my performance is being changed compared to, uh, depending upon the type of patient I'm dealing with. Whereas if I blind it, if I don't tell the surgeon who the patient is, who isn't the patient who the control is, then there's no way that the surgeon can change his performance and that, and that completely gets rid of the performance bias. So when I blind, er, surgeons, when I blind the patients, when I blind other people from whether they're getting the treatment, they're not getting the treatment. I'm making the research more powerful, more robust. So more blinding, more valuable your clinical trial will be. So the way you can blind, there are different ways you can blind the patient. So the patient will not know whether they are a, they're getting a placebo or whether they're getting the actual drug. You can blind the surgeon, you can blind other clinicians, you can blind the data collectors. People who collect the data, you can blind outcome assessors, you can bind the data analyst or you can even blind the people who write up the research. Now, the type of blinding or the feasibility, how much you can blind really depends upon the intervention. So if I'm uh if I'm trying to look for a, uh doing a trial on a drug, I can blind it with a placebo, just give them an empty tablet if I'm blinding it. If I, if my intervention is a surgery, like I said, it's very hard to blind the surgery because the patient will know whether, you know, you can't really hide the surgery. They know that they, they're taking up for surgery because they have the disease. But there's also something called the shams um surgery. Now, a sham surgery is nothing. But when a patient is taken up to the surgery and just a simple incision, skin in incision is made, but the surgery is not performed because they don't have the disease. So here, the way we do that is because we're blinding the patients. We're trying to have every, let everyone have the surgery and we're trying to see if it makes any difference. But you can imagine the amount of ethics that will go behind you when you just take off a patient, just for the sake of a surgery, do a skin incision and then send them back without doing any surgery. An example of a, a sham surgery would be something that, um, that I touched upon this is from the New England Journal of Medicine. And this was a trial that was done, I think in the two thousands, early, two thousands. And this completely challenged the treatment of osteoarthritis in orthopedics because what they did was they took up every patient who had, who did not have, who had knee pain or knee problems. And they try to see whether surgery does surgery really make a difference in their knee problems or in the osteoarthritis. And they involve shunt surgery. So they basically took everyone to surgery, those who had osteoarthritis, half of them, they did the arthroscopy, those who had osteoarthritis, they didn't do anything, they just made the incision, they sent them back, they told them we did the surgery for you. And then over over years, they looked for the clinical outcome, whether there was there any difference in their pain relief? Was there a difference in their quality of life in their mobility, were they able to move around, play around, do their normal life functions? And they found out there was literally no difference between a painkiller and an arthroscopic surgery. And that completely challenged the treatment that was going on because everybody thought whoever had osteoarthritis, if they take them up for arthroscopy, they will have a better outcome. This trial came out saying that there's no difference. And since then, the level of arthroscopy, the amount of arthroscopies that has been done in the orthopedics has dramatically reduced because they found out it's not really doing much of a difference. But you can imagine the amount of ethics that this trial had to go through because you're putting patients through anesthesia, you're putting them through the your they're going under your scalpel but not getting any kind of intervention in the placebo group. So this is an example of a sham surgery. Now, the the last part that I want to sort of touch upon is the types of clinical trials that can go on. So there are so many different types of clinical trials. Um But the I think they can be broadly divided into two different groups. So you've got the treatment trial, uh in terms of what you're trying to find the trials on treatment trials, which is what I have been discussing about where you have a medication, you intervene, you try to see if it's creating any kind of difference, you can have something called the prevention trials. So when you're trying to prevent a, a disease or prevent something, like for example, birth controls. Are you trying to find out? Um if that prevention is better or not, you can have a screening trial, a screening trial is nothing. But if you're trying to find out a particular diagnostic tool or a screening tool that you are using to see if you can find as many patients who have the disease. Like for example, if a pap smear, so a pap smear is something that's usually done for a woman above the age of 25 or 27 um around the world. And they do take a small um cotton swab or a cervical swab and they make a small swab around the cervix of women. And they basically try to see if they, if they have any chances of developing cervical cancer. So that screening that that's a screen screening type of tool and you can do a trial on you on it and see if you were able to screen patients at an early stage of their disease. Then you've got the diagnostic trial. This is when you're trying to find out the effectiveness of any kind of diagnostic tool, like a like scans or blood tests or things like that. Then you've got the supportive care trial. This is something quite interesting and it has emerged uh and has become more popular in the recent years, a supportive care trial is nothing that whether you're able to make a quality of life of a person, maybe who they might be, uh, uh, maybe like a survivor of a, a chronic disease, like a cancer patient. And you're trying to see whether you're able to give them as much support as you can, whether it's holistic, like, for example, through counseling, through therapy, or is it making their day to day life comfortable, like walking around? So you're trying to see if you're able to do, make that, make any difference in terms of the supportive care you're giving, you can do a trial on that. So that's the ty different types of clinical trials. But the ones that I really wanted to touch upon are superiority, equivalence and non infer. And this is something that you will come across, er, quite commonly used terminologies when you're looking at um clinical trials, when you reading different papers. So what are the different types of superiorities and equivalence and non infer? So let's take an example. This, it will be quite easy to understand with an example. So if I'm doing a drug, if I have a AAA nice little drug in front of me, and I'm thinking I'm going to give out this drug and I'm gonna compare it with someone who doesn't take the drug. And what I'm trying to say, see is I'm trying to see if this drug is at least as good as the one that's already, um, been going on that's already been given in the treatment. So, the way I'm trying to find out is if the new drug is at least as good as a control that's known as a non inferiority trial, I'll explain that with an example. A superiority trial is, I've got a drug in front of me and I'm thinking this drug is definitely better than what's already going on. What's already been given out in the market or what's already been giving out, been uh used in the hospitals. That's a superiority trial. An equivalent trial is, this drug is trying to say the, I mean, this trial, I was trying to say this drug is as equal, equally effective as a medication that's already been prescribed. So let's go through each one of them with an example. It's, it's a, it's a bit of a, um, ad uh, um, a concert that takes a bit of time to wrap your head around, but it's quite easy when you get the hang of it. So I've got a clinical trial in front of me, which is an example of a non inferiority trial. So what they did here is they, they've got a, a drug called semaglutide and they gave these drugs to overweight or obese adults and they gave them once a week and they gave them for 80 weeks to see if there was any difference in their weight loss. Looking at the BM ice. Now, the way they did that was, they tried to see if they were able to make any difference. They had semaglutide group. They also had a placebo group and they, they were only trying to find out if the semaglutide can make any difference. Maybe if it made a difference, then they will add it to the treatment list. So this might not be the first treatment that you will give. But this could be an optional treatment. For example, if the first treatment isn't there, this will be an option for them. That's an example of a non inferiority trial. Now, the next type is a superiority trial. Now, here, what I'm trying to say is I think this drug is much better than what's already what's being prescribed to patients right now. So an example is SGL T two inhibitors, I think um I think it was DAPA. Yeah, Dapa Gliflozin was a SGL T two D inhibitor that was given out to patients to see if there was any differences in the cardiovascular or renal outcomes in type two diabetic patients. So, excuse me, they gave DA to half the patients in the treatment group, they gave the second half nothing. And what they wanted to do is they wanted to see if da made a significant difference. And unfortunately, it did, they found out that Dapagliflozin actually reduces the amount of cardiovascular and renal um uh complications in diabetic patients. And this, the main aim of it was to see whether they can add this to at the top of the treatment list saying that this is probably the better treatment option compared to what's already been given in the protocol. And the last one is equivalence. Now, equivalence trial is again an interesting trial because we're not trying to say this is better. We're not trying to say this can be another treatment option. We're trying to say this is equal. So if in your hospital, you run out of whatever medication you're giving, you can give this as well because this is just as equally effective as what you have already been giving. An example of an equivalence trial is um a trial that was done in Kenya. And this was basically trying to focus on women who've had abortions. So when a woman has an abortion, we have to make sure obstetricians have to make sure that all the pregnancy products comes out of the uterus or else it will go into complications. And the way they do that is they can do a surgery, uh a a minor surgical procedure called DNA dilatation and evacuation where they manually, you know, intervene, uh dilate the uterus and remove any fetal products that are left inside or they can give a medication which is uh miSOPROStol. And what that does that contracts the uterus and expels out the, the, the the pregnancy products. So they wanted to see if that was equal. So, sort of me, sort of an obstetrician um intervening and doing a DNE which is a procedure and it can, can involve a lot of pain, a lot of uh you know, post procedural care if I give them a miSOPROStol, do you think if it, I think it's just as effective as that? And they found out it is miSOPROStol is just as effective as a DNA in, in this Kenyan clinical trial. So that's an example of an equivalence trial which which is trying to say, yeah, there is definitely uh they, they definitely as, probably will be as equal as that. So these are the three different types of clinical trials that you will come across when you are trying to read different papers. So I think, II hope that wasn't um too heavy or um a lot to take in any questions so far. OK. So we're almost done. The last part that I wanted to touch upon before we end the session would be clinical phases of clinical trials. Now, this is um very interesting and you as a uh a junior doctor or at uh um someone who's working in a team should be really aware of what, what phase your clinical trial goes into. So if I've got a medication in front of me and I've got all the approval as a as a researcher, I've got all the ethical approvals everybody has approved and they've all given green light. I'm good to go ahead. I have to go through these different phases and it's really important we understand what the different phases are. So the first phase, it just starts off with me with a couple of healthy volunteers that I volunteer that I gathered through advertising and attracting them to the study. And I just give them the medication. Now, I do this, I do this, uh, very closely. I put them in a clinical, uh, lab or in a, a clinical, uh, sorry research lab and I give them the medications and I wash them very carefully to see if they've been, they're developing any kind of outcomes. Now, here, I'm trying to see, look for safety of that drug, whether that drug is quite good, er, is safe for that, for, for humans. And that's phase one. last week I think we looked at, I think you might have been, uh, shown a video about the North Wick Park clinical trial. It's a very interesting clinical trial. I think you should definitely look it up the North Wick Park. It's a trial that was done in the UK. Um, and they were trying to really find out, look for a drug, um, to treat leukemias and where it went wrong was in phase one. So they, uh, and, but it really completely dramatically changed the way we looked at the ethic ethics of involving humans because what they basically did is they, they lined up 10 patients in one room, they gave them more medications, one after the other went and had a coffee and then they came back and they realized one after the other was crashing and this happened because they, they, they gave the medications in a staggered manner. You know, they didn't wait for one. Uh, they didn't wait for one pe one person to see if they've developed any disease. They just gave it one after the other and they realized that one had 20 minutes to crash, another one had 10 minutes to crash. Another one had five minutes to crash. And it was such a tragic, um, it was a disastrous clinical trial because one of them died and the rest of them were told that they will develop cancer, um, at some point in their lives because of this drug. And that was because the safety, um, was not regulated behind, uh, human involvement in a clinical trial. So that's, that, that's something that happened in phase one. Now, once I've, I've gone through phase one and goes into phase two. Phase two is nothing. But basically, I recruit 100s of people and I give out this drug because I think it will probably be effective. And here, I'm trying to look for mainly the dosage, what is the safety dosage that I can give this medication in? Thus, phase two is what, what is used for, um, trying to effect, look for the effectiveness at treating diseases and also looking for the particular dose. Now, once you've got, you've gone through phase two, which will go for months, you go into phase three, phase three goes for years where I recruit 100s and 100s of patients. And here what I'm trying to look for is II, give them all the medications and I try to see if I can look for any side effects, if there's any kind of outcome adverse out um effects that might be involved in terms of this drug. And once that's gone, then you go into phase four, which is you put that in your treatment or in your protocols and you start prescribing this on a regular basis. So again, you can see that clinical trials isn't something that's done over a year or two, it's something that happens for years and years and years and for a medication. So literally everything that we give out as doctors, everything that we prescribe to our patients has gone through all these different phases of clinical trials has had loads of clinical trials behind it. And that's the reason we're giving it because this is evidence based medicine. We as doctors um practice in our clinical settings. So I hope you are able to get an a clear idea of what clinical trial is. Um what are the different types of trial uh trials that is involved? And um one of the things that we need to keep in mind, so that sort of brings us to the end of today's session. If you've got any questions, feel free to pop them in the chat box as well. So just a quick reminder, we do have uh of all the sessions that are coming up. So we've got our next session that's looking at the different types of levels of evidence and all the different types of research bias and how we can reduce the research bias. I think today I touched upon research bias and clinical trials, I'll, I'll explain about the different types of research biases uh and related to other types of re uh research designs as well. So I've got the dates of that confirmed and we'll also look at the good clinical practice and declaration of Helsinki. This is something that's done in the NHS quite commonly. So um that will be a session on that as well. So any questions feel free to pop in, in the chat box? So while we wait, um can I also kindly ask you to fill in the feedback form of today's session that would be really useful for us as we're trying to improve um our teaching methods and trying to make it as interesting as possible. So if I could ask you to fill in the feedback forms as well, that would be great. So if we've got any, um if we don't have any questions, I think we can end today's session here. OK. So yeah, we'll talk about research by stim. So thank you for uh listening. Um If you've got any questions, please just s stay back, we can discuss or else I think we can all finish it off here. Thank you for attending uh today's session and I hope to see you guys in the next session. Thank you. Take care.