Statistics and Market access – from foes to friends

Transcript

Statistics and Market access – from foes to friends

00:00:00.640 –> 00:00:16.855
You are listening to the Effective Statistician Podcast, the weekly podcast with Alexander Schacht and Benjamin Piske designed to help you reach your potential, lead great science, and serve patients while having a great work life balance.

00:00:23.315 –> 00:00:39.175
In addition to our premium courses on the Effective Statistician Academy, we also have lots of free resources for you across all kind of different topics within that academy.

00:00:39.635 –> 00:00:50.055
Head over to www.theeffectivestatistician.com and find the academy and much more for you to become an effective statistician.

00:00:50.930 –> 00:01:01.670
I’m producing this podcast in association with PSI, a community dedicated to leading and promoting the use of statistics within the health care industry for the benefit of patients.

00:01:02.290 –> 00:01:14.605
Join PSI today to further develop your statistical capabilities with access to the ever growing video on demand content library, free registration to all PSI webinars and much, much more.

00:01:14.985 –> 00:01:23.670
Head over to the PSI website at psiweb.org to learn more about PSI activities and become a PSI member today.

00:01:31.045 –> 00:01:33.865
Welcome to another episode of the effective statistician.

00:01:34.325 –> 00:01:43.445
Today, I’m super happy to have someone on the podcast that already has been on the show, but now in a new role.

00:01:43.445 –> 00:01:44.185
Hi, Necdet.

00:01:44.245 –> 00:01:45.065
How are you doing?

00:01:45.640 –> 00:01:46.380
Hi, Alexander.

00:01:46.440 –> 00:01:46.920
I’m good.

00:01:46.920 –> 00:01:47.320
I’m good.

00:01:47.320 –> 00:01:48.200
How are you doing?

00:01:48.200 –> 00:01:49.260
It’s been a while.

00:01:49.800 –> 00:01:55.500
It’s been a while since you’ve been on the show, and there has been some changes on your end.

00:01:55.560 –> 00:01:59.745
Let’s talk shortly about this and, introduce yourself and what you’re doing now.

00:01:59.985 –> 00:02:00.225
Yes.

00:02:00.225 –> 00:02:00.705
Of course.

00:02:00.705 –> 00:02:02.485
So I’m, Necdet Gunsoy.

00:02:02.785 –> 00:02:07.925
I think the last time that I spoke on the podcast was at PSI.

00:02:08.145 –> 00:02:11.265
I feel like saying 2018, maybe 2019.

00:02:11.265 –> 00:02:16.040
I I can’t remember, but it was about, subgroups, I think.

00:02:16.040 –> 00:02:17.020
That was the episode.

00:02:17.240 –> 00:02:23.660
So since then, I’ve actually shifted more into working in HTA and market access.

00:02:23.720 –> 00:02:26.620
I was in GSK back then, and then I moved to AbbVie.

00:02:26.920 –> 00:02:43.460
But recently, I left AbbVie, and I’ve set up my consultancy company called EviMed, and we are a kind of boutique technical consultancy which specialize in health economics and outcomes research, real world evidence, HTA and market access.

00:02:43.680 –> 00:02:44.180
Yeah.

00:02:44.400 –> 00:02:50.640
Which is quite an interesting perspective because that is the topics that we’ll talk about today.

00:02:50.640 –> 00:03:10.885
You have now worked on both sides, on the statistics side as well as on the market access side, And you support also both sides with your business, which I think is brilliant because there’s a very often a lot of struggle between market access organizations and statistics organizations.

00:03:11.505 –> 00:03:18.940
And me having worked as an HDA statistician for quite a long time, I know what I’m talking about.

00:03:20.520 –> 00:03:26.060
So why do you see these organizations very often struggle with each other?

00:03:26.395 –> 00:03:30.975
It’s complex really, but I think it really boils down to a few key things.

00:03:31.195 –> 00:03:49.690
You know, I think when you’re a statistician and if, let’s say, you’re not necessarily split in different functions within statistics, generally speaking, the request for mark access or the preparation for HTA reimbursement submissions, it starts often at the same time that, you know, the statistician is busy with regulatory submissions.

00:03:49.690 –> 00:03:58.335
So actually running all the clinical trial analysis that would go into the regulatory submissions or in the course of the regulatory submission when you’re getting questions and you have to all of these requests.

00:03:58.335 –> 00:04:09.235
Perhaps one of the big struggles is always getting these requests when you are being told from other stakeholders that, you know, regulatory is the top priority and you can’t work on anything else.

00:04:09.375 –> 00:04:14.390
Another thing that’s confusing for statisticians, right, is they’ll get a lot of requests.

00:04:14.390 –> 00:04:14.630
Right?

00:04:14.630 –> 00:04:30.515
There’ll be a lot and I do mean a lot sort of maybe like thousands of tables that the mark access team is asking for things requests for lots of different countries And often this leads to a lot of confusion from the stats end because, you know, they’re thinking why is there so much?

00:04:30.515 –> 00:04:35.075
Why is it you know, on the market access side, it’s sort of the flip you know, the other side of the coin.

00:04:35.075 –> 00:04:35.315
Right?

00:04:35.315 –> 00:04:41.500
For them, obviously obviously, like, you can’t have patients can’t have access to a medicine without regulatory approval.

00:04:41.500 –> 00:04:41.980
Right?

00:04:41.980 –> 00:04:44.140
But equally, you can have regulatory approval.

00:04:44.140 –> 00:04:46.720
If it’s not reimbursed, the patients don’t get it either.

00:04:46.780 –> 00:04:56.145
And so, you know, it’s a very important priority as well to ensure that we’re doing reimbursement submissions as quickly and as early as possible so that patients get access as soon as possible.

00:04:56.145 –> 00:04:56.385
Right?

00:04:56.385 –> 00:04:57.825
That makes sense.

00:04:57.825 –> 00:05:09.600
There’s always this kind of dynamic between kind of regulatory and reimbursement that always kind of causes a lot of anxiety between different functions, a lot of confusion, a lot of stress.

00:05:10.140 –> 00:05:15.660
And the last thing, and I think this is on both sides as well, is just the foundational knowledge.

00:05:15.660 –> 00:05:16.160
Right?

00:05:16.540 –> 00:05:27.515
Being in statistics, you know, I think I experience statisticians don’t really understand how mock access necessarily works, how reimbursement submissions work

00:05:27.755 –> 00:05:27.995
Yeah.

00:05:28.315 –> 00:05:31.935
What evidence is needed for them, what are the different steps.

00:05:32.315 –> 00:05:37.260
And that fuels the idea that they’re confused and they don’t understand why these are coming from.

00:05:37.340 –> 00:05:53.935
On the market access side, maybe what they lack is a little bit understanding around how stats work more like in terms of processes and, you know, how maybe something simple can actually take a lot of time to do because of the systems, approvals, all of these kinds of things.

00:05:53.935 –> 00:05:56.655
You know, I hear a lot of kind of folks in Mark Access.

00:05:56.655 –> 00:05:58.415
They’ll say, oh, it’s just the click of a button.

00:05:58.415 –> 00:05:58.655
Right?

00:05:58.655 –> 00:06:00.255
You know, it’s like a couple of analysis.

00:06:00.255 –> 00:06:01.535
All they have to do is click a button.

00:06:01.535 –> 00:06:02.915
Why does it take three months?

00:06:03.980 –> 00:06:09.200
And so it’s that kind of mutual lack of understanding a little bit makes it, very challenging as well.

00:06:09.740 –> 00:06:09.980
Yeah.

00:06:09.980 –> 00:06:17.615
I think one of the misunderstandings are all the acronyms and abbreviations and terms that I use.

00:06:17.675 –> 00:06:26.175
As you started to introduce yourself, I was thinking like, oh my god, maybe there’s a lot of confusion about all these terms.

00:06:26.395 –> 00:06:26.895
Yeah.

00:06:27.115 –> 00:06:31.455
So let’s shortly walk through what that actually means.

00:06:31.610 –> 00:06:35.310
The first abbreviation you mentioned is HTA.

00:06:35.770 –> 00:06:37.310
What is actually HTA?

00:06:38.250 –> 00:06:40.350
HTA is health technology assessment.

00:06:40.650 –> 00:06:43.470
Generally refers to the process of trying to get reimbursement.

00:06:43.530 –> 00:06:43.995
Right?

00:06:44.075 –> 00:06:45.515
So you’ll do an h t a dossier.

00:06:45.515 –> 00:06:46.895
People say h t a dossier.

00:06:47.115 –> 00:06:49.055
Sometimes they’ll say a reimbursement dossier.

00:06:49.355 –> 00:06:52.955
Pedanticly speaking, h t a probably refers to the t a agency.

00:06:52.955 –> 00:06:58.175
So every country will have an agency that assesses the reimbursement of products.

00:06:58.400 –> 00:07:00.960
They’re not necessarily an h t a agency.

00:07:00.960 –> 00:07:17.115
So when we say h t a agency, it’s probably like a mature, evolved agency that has a very set and defined process for evaluating the efficacy, safety, and sort of pharmacoeconomic value of a particular treatment.

00:07:17.255 –> 00:07:22.615
People would interchangeably refer to HTA or reimbursement or these kinds of terms.

00:07:22.615 –> 00:07:23.115
Yeah.

00:07:23.620 –> 00:07:28.500
And HTA agencies are, for example, in The UK, it’s NICE.

00:07:28.500 –> 00:07:29.960
In Germany, it’s ICBIC.

00:07:30.340 –> 00:07:32.040
In France, it’s HAS.

00:07:32.420 –> 00:07:33.080
That’s right.

00:07:33.860 –> 00:07:38.295
In Canada, I think is c h d t h.

00:07:38.435 –> 00:07:40.355
So it used to be CATHITH, but it’s changed now.

00:07:40.355 –> 00:07:41.715
It’s, called the CDA.

00:07:41.715 –> 00:07:42.755
So they’ve joined.

00:07:42.755 –> 00:07:43.575
They’ve reorganised.

00:07:43.955 –> 00:07:45.075
It’s a different agency.

00:07:45.075 –> 00:07:45.575
Yeah.

00:07:45.715 –> 00:07:46.115
Yeah.

00:07:46.115 –> 00:07:48.915
So you will have acronyms from all over the place.

00:07:48.915 –> 00:07:52.970
And in The US, there’s an organization called ISA.

00:07:53.350 –> 00:07:55.050
It’s also quite impactful.

00:07:55.510 –> 00:08:04.730
Since they named themselves ISA isn’t really helpful because that is also an acronym for something else, but that’s, that’s another topic.

00:08:04.870 –> 00:08:07.775
These are the HTA organizations.

00:08:08.075 –> 00:08:15.295
And these are similar to FDA or EMA, but they all exist just on a local level.

00:08:15.355 –> 00:08:19.215
So you don’t have any kind of global organizations there.

00:08:19.275 –> 00:08:22.870
I think that leads also to the next challenge.

00:08:23.730 –> 00:08:30.230
Market access, is that actually just a local function, or is that also a global function?

00:08:30.930 –> 00:08:31.250
Both.

00:08:31.250 –> 00:08:36.875
There’ll be market access generally at the global, regional, local level.

00:08:37.095 –> 00:08:43.655
And, yes, mark access is, let’s say, vision is to provide access for patients to new medicines.

00:08:43.655 –> 00:08:43.815
Right?

00:08:43.815 –> 00:08:44.935
That’s their ultimate goal.

00:08:44.935 –> 00:08:48.390
But there’s a lot more to mark access than just the HTA.

00:08:48.390 –> 00:08:48.630
HTA.

00:08:48.630 –> 00:08:48.870
Right?

00:08:48.870 –> 00:08:49.990
Maybe that’s the end of it.

00:08:49.990 –> 00:08:50.230
Right?

00:08:50.230 –> 00:08:52.890
That’s at the end you’re getting the reimbursement.

00:08:53.270 –> 00:09:04.090
Still goes on afterwards because then there’s thinking about competitive positioning, kind of all of the follow-up work to make sure that you are constantly disseminating the value of your treatment to patients.

00:09:04.205 –> 00:09:32.010
The market access concept starts very early on in the process from even when you’re deciding whether or not you’re investing in an asset or not because, you know, part of what market access would do is kind of define a strategy, a market access strategy for a product, and it starts as early as phase one, even preclinical I’ve experienced, where you try and think about the potential value for treatment for patients might be of this drug when it’s commercialized in, you know, five, ten years depending on what you’re looking at.

00:09:32.010 –> 00:09:41.225
But so there’s a strategy in terms of, you know, how we achieve access and really HTA is more like the kind of almost the end game where you executing that submission.

00:09:41.525 –> 00:09:51.050
Of course, with HTA it’s, you start early as well because clinical trial design, you need to think ahead of whether your clinical trial design is addressing the needs of agencies.

00:09:51.990 –> 00:10:08.605
Just like with regulatory bodies, you go for early scientific advice with agencies to kind of understand, you know, what would be relevant comparators, what would be endpoints that they’re interested in, what are the value drivers from a payer perspective.

00:10:08.665 –> 00:10:19.340
So again, we refer to payer as the organisations who pay for treatments and thinking about all of these things would be kind of the market access role, per se.

00:10:19.340 –> 00:10:22.160
And then when you have this, you have, like, a global strategy.

00:10:22.220 –> 00:10:22.700
Right?

00:10:22.700 –> 00:10:27.040
And obviously, you have a global strategy which has kind of maybe your value proposition.

00:10:27.100 –> 00:10:27.980
Like, what’s the value?

00:10:27.980 –> 00:10:29.900
How do you communicate the value of this treatment?

00:10:29.900 –> 00:10:44.875
And then obviously, we have then from a regional and local level, how that is actually operationalized will vary from country to country because payers are different, regulations are different, the environment is different, guidelines are different, and so that’s how the local part works.

00:10:45.130 –> 00:10:50.650
There’s another abbreviation that I hear very often, p r a Mhmm.

00:10:50.730 –> 00:10:52.590
Pricing reimbursement and access.

00:10:53.130 –> 00:10:56.250
This acronym speaks also to the other parts of it.

00:10:56.250 –> 00:10:56.650
Mhmm.

00:10:56.650 –> 00:10:59.035
It’s not just the getting access.

00:10:59.035 –> 00:11:01.375
It’s also about the reimbursement piece.

00:11:01.515 –> 00:11:09.855
And of course, setting the price is a very delicate thing because, that is not as easy as setting a price for any other products.

00:11:09.995 –> 00:11:19.720
There’s high dependencies between the different markets and prices will vary quite a lot and it can also vary over time quite a lot.

00:11:20.260 –> 00:11:20.500
Yeah.

00:11:20.500 –> 00:11:24.740
Pricing is very, very complicated and variable across countries.

00:11:24.740 –> 00:11:26.420
The rules are different in each country.

00:11:26.420 –> 00:11:27.800
The mechanisms are different.

00:11:28.215 –> 00:11:30.295
The the evidence supporting pricing is different.

00:11:30.295 –> 00:11:31.755
The methods used are different.

00:11:31.815 –> 00:11:35.495
But pricing also is this is kind of the same philosophy as market access.

00:11:35.495 –> 00:11:45.150
You would generally have a strategy on pricing, which is global, and then those would kind of be locally translated locally and how it applies locally.

00:11:45.530 –> 00:11:52.430
But, again, it starts with a global vision, and it kind of filters through to the regions and to local countries.

00:11:52.570 –> 00:11:53.070
Yeah.

00:11:54.045 –> 00:12:06.385
Then these two other acronyms that you mentioned, RWE and Health Outcomes and Research or Health Economics and Outcomes Research, HEOR.

00:12:07.165 –> 00:12:07.985
That’s right.

00:12:08.120 –> 00:12:11.580
What is that compared to PRA or market access?

00:12:12.040 –> 00:12:20.775
So h o r, maybe h o r, all the way perhaps represents more of the, let’s say, the scientific arm of what is market access in general.

00:12:20.775 –> 00:12:25.495
I mean, people may disagree or agree, but so HUI is two bits.

00:12:25.495 –> 00:12:25.735
Right?

00:12:25.735 –> 00:12:28.315
There’s the health economics and there’s the outcomes research.

00:12:28.935 –> 00:12:31.495
So the health economics side is basically what it is.

00:12:31.495 –> 00:12:31.735
Right?

00:12:31.735 –> 00:12:33.915
It’s kind of trying to merge health and economics.

00:12:33.975 –> 00:12:38.500
It’s trying to demonstrate the value of treatments more in economics terms.

00:12:38.880 –> 00:12:42.980
There are different types of tools that would be used to kind of demonstrate that.

00:12:43.440 –> 00:12:52.175
You may have heard of cost effectiveness models, which is trying to calculate the incremental cost effectiveness ratio, which is the, the other thing for ISA.

00:12:52.875 –> 00:13:01.775
So that looks at, you know, how much extra does a new drug cost versus how much benefit is it providing, how much does it prolong the quality of life of patients.

00:13:02.460 –> 00:13:09.840
Some countries have thresholds in terms of how much they’re willing to pay for a certain improvement in quality of life for patients.

00:13:10.300 –> 00:13:14.160
And that would be the basis of kind of setting the price in those countries.

00:13:14.565 –> 00:13:18.805
You have other tools, kind of budget impact models or cost comparison models.

00:13:18.805 –> 00:13:21.065
But anyway, that’s kind of the health economic side.

00:13:21.205 –> 00:13:26.485
The outcomes research side is more focused on trying to quantify the impact on patients.

00:13:26.485 –> 00:13:26.725
Right?

00:13:26.725 –> 00:13:46.085
So it goes from things like burden of illness to patient reported outcomes, patient experience, all these kinds of things that are not quite kind of hard efficacy endpoints, let’s say, but more thinking about the quality of life aspects of patients and also outcomes in terms of kind of long term outcomes of disease.

00:13:46.085 –> 00:13:58.185
You know, it’s a little bit of a mix of maybe the epidemiology as well, but it’s more that that outcomes type of research can be using clinical trial data, but would use kind of other sources of data as well, you know, observational data, etcetera.

00:13:58.520 –> 00:14:02.620
And then real world evidence is sort of like, let’s say a piece of all of this as well.

00:14:02.680 –> 00:14:10.380
I think we can simplify it by saying real world evidence is any kind of research that is done on data from the real world per se.

00:14:10.615 –> 00:14:23.815
But generally, when people refer to real world evidence, it would be, you know, analysis of data maybe that was collected for not necessarily the purpose that you’re using it for, but data that is available there such as things like claims data in The UK.

00:14:23.815 –> 00:14:31.840
You have, like, hospital episodes, statistics, these kinds of things that you can and that you could leverage to do answer some research questions using that data.

00:14:31.900 –> 00:14:36.080
Initial purpose wasn’t specifically designed for this, but it can help answer those questions.

00:14:36.140 –> 00:14:50.635
And there’ll be a lot of real world evidence out there both in terms of health care data, but also different companies doing surveys with patients or registry studies set up by universities, for example, or patient organizations or, you know, these kinds of things.

00:14:50.635 –> 00:14:55.470
There are many different sources out there that you can use in that kind of reward evidence umbrella.

00:14:55.610 –> 00:14:55.930
Yep.

00:14:55.930 –> 00:15:01.870
And all these organizations, all these groups working on these set up differently in the different companies.

00:15:02.250 –> 00:15:05.070
But very often you will have two branches.

00:15:05.370 –> 00:15:12.785
One is more kind of the scientific part of it and the other part will be the more business side of it.

00:15:13.885 –> 00:15:24.600
And as statisticians you will most likely more work with the scientific part because they will create the HCA dosiers for example.

00:15:25.380 –> 00:15:37.075
Now when we don’t work well together what can ultimately happen if statistics, organizations, and these market access organizations don’t work well together?

00:15:37.075 –> 00:15:37.575
So

00:15:38.115 –> 00:15:39.235
probably three things.

00:15:39.235 –> 00:15:39.735
Right?

00:15:39.955 –> 00:15:46.775
The first really important thing would be not being able to have effective prioritization discussions.

00:15:47.075 –> 00:15:47.315
Right?

00:15:47.315 –> 00:15:58.210
Because when you don’t understand the why and the what and the how mutually, you can’t really have a prioritization discussion.

00:15:58.590 –> 00:16:14.745
If statisticians don’t necessarily understand, you know, have a foundation understanding of how reimbursement submissions work, what evidence goes in there, it will be very difficult for them to then negotiate competing priorities with if they’re working on regulatory or other work that they’re doing.

00:16:14.885 –> 00:16:23.100
Equally, I think that in market access, they might tend to kind of request everything they need or everything they might need in one go.

00:16:23.560 –> 00:16:32.540
And if they’re not pushed to have those prioritization discussions, it would be very they wouldn’t necessarily be able to communicate what are the priorities, effectively.

00:16:32.725 –> 00:16:40.985
And it’s maybe a lack of understanding of processes as well, right, in terms of how then those requests are managed and how they’re fulfilled in the stats organization.

00:16:41.445 –> 00:16:44.165
So that leads to kind of this inefficient handling of requests.

00:16:44.165 –> 00:16:44.665
Right?

00:16:44.885 –> 00:17:00.260
So let’s say you have a thousand tables to do and, maybe you need to write an analysis plan, get it approved, all of the stuff on the stats side and then you begin delivering on results and you’re doing this in a way that, let’s say, might be most efficient in your stats organization.

00:17:00.480 –> 00:17:06.835
So maybe you get safety done first and you send the safety results to mark access and say, well, why are you sending me safety?

00:17:06.835 –> 00:17:07.955
I don’t want safety now.

00:17:07.955 –> 00:17:08.755
I don’t need this.

00:17:08.755 –> 00:17:09.255
Right.

00:17:09.715 –> 00:17:15.655
And and actually they wanted something else first or maybe they possibly never even needed this stuff that you delivered.

00:17:15.875 –> 00:17:26.160
And that’s the inefficient side because, obviously, you know, everyone is trying to do things as efficiently as possible, but if they don’t understand what the priorities are, then it’s going to be inefficient in the end.

00:17:26.160 –> 00:17:37.625
And, ultimately, like, with all these in it lack of prioritization, inefficiencies, the worst thing that can happen is that you you end up delaying a reimbursement submission, which you could have easily avoided.

00:17:37.625 –> 00:17:37.865
Right?

00:17:37.865 –> 00:17:40.525
Because everyone’s working at very tight timelines.

00:17:40.585 –> 00:17:45.720
So even a couple of weeks delay or three weeks delay on something could mean a delay to a submission.

00:17:46.100 –> 00:17:53.960
And that ultimately means that patients are suffering from that, right, because they don’t get the treatment as early as they could have.

00:17:54.020 –> 00:17:54.520
Yep.

00:17:54.580 –> 00:17:56.440
And and that’s what we really want to avoid.

00:17:56.500 –> 00:17:58.600
I’ve seen that, and I’ve seen that happening.

00:17:59.115 –> 00:17:59.515
Yeah.

00:17:59.515 –> 00:18:05.855
Delaying reimbursement submission very often means delaying the launch of a new compound.

00:18:05.995 –> 00:18:19.140
So I’ve seen that a new drug couldn’t be launched in Germany because pricing very often depends on Germany, could therefore also not be launched in many other European countries just because of that.

00:18:19.360 –> 00:18:36.595
You have optimized everything to get regulatory approval, and then you have an approved drug that you can’t sell, which of course is a nightmare from a commercial point of view and can really increase then the pressure on getting everything ready.

00:18:37.295 –> 00:18:44.030
There’s also very often confusion about terms between these two functions.

00:18:44.090 –> 00:18:51.390
And I know of a company, a very big one, where they got confused about the term data.

00:18:52.875 –> 00:19:00.895
The statistician said, yeah, we’ll get the data by June.

00:19:01.995 –> 00:19:09.940
And then the market access people were planning everything and at the June they would start with stuff.

00:19:10.880 –> 00:19:30.305
However, the statistician was thinking we will get this data from an external organization, then we will have three months to clean it, then we will have three months to work on it for the regulatory submission, and then we will have three months to prepare it for market access.

00:19:30.925 –> 00:19:52.475
So the time delay was actually nine months between what the market access people perceived as data actually the results in forms of summary statistics and summary data and the statistics team thinking about the actual by patient level data getting that.

00:19:52.855 –> 00:20:04.290
And that is an example of not really communicating well, of this kind of superficial communication, not really understanding what is happening when.

00:20:04.990 –> 00:20:10.850
And that, of course, led to a huge kind of debate within that company.

00:20:11.550 –> 00:20:16.335
VPs got involved on why there is this huge delay and things like that.

00:20:16.655 –> 00:20:19.475
And you don’t wanna be in in that situation.

00:20:19.775 –> 00:20:31.455
And and that’s an interesting situation because if you have that conversation within a technical environment, maybe everyone would probably assume that means when you get the data, not when the analysis is done.

00:20:31.455 –> 00:20:31.860
Right?

00:20:32.020 –> 00:20:33.460
You know, I guess it’s the language thing.

00:20:33.460 –> 00:20:33.780
Right?

00:20:33.780 –> 00:20:39.220
And part of this mutual understanding is also knowing the language of each other.

00:20:39.220 –> 00:20:39.720
Right?

00:20:39.780 –> 00:20:54.825
Part of that is then the lack of communication is a little bit from the lack of understanding, right, from both sides because, you know, someone in mark access should know that maybe receiving data doesn’t mean completion of analysis in in terms of a technical term when when you would speak technically.

00:20:55.045 –> 00:20:55.205
Yep.

00:20:55.365 –> 00:21:05.820
But equally, I think from the statistician side, you need to know that you need to know that you have to explain these things very clearly and be very clear on the timelines associated with each step because they don’t know.

00:21:05.820 –> 00:21:06.140
Right?

00:21:06.140 –> 00:21:07.340
Mark access or yeah.

00:21:07.340 –> 00:21:14.000
They need that understanding that they know that Mark access doesn’t know about this, and they have to tell them very simply the whole communication.

00:21:15.005 –> 00:21:18.065
So how can we avoid all these kind of struggles?

00:21:18.525 –> 00:21:21.185
Because they are often there.

00:21:21.245 –> 00:21:25.905
And what can we do to smoothen this relationship?

00:21:27.080 –> 00:21:31.900
So, really, I think the first thing is the education and the mutual understanding.

00:21:32.280 –> 00:21:50.455
And I think this applies for every function, but for statisticians specifically, statisticians, they need a foundational understanding of kind of how pricing and reimbursement processes work, how HTA submissions are done, what the requirements are, and, of course, what the methodologies are.

00:21:50.455 –> 00:21:53.755
But that’s, let’s say, specific to statisticians, they need to know that anyway.

00:21:53.815 –> 00:22:11.855
But aside from the methodology, which I think a lot of statisticians kind of focus on that, obviously, because they’re the people sometimes running the analysis, they need to understand all of these processes because that really would help them then have those conversations with their mock access HUR, epi colleagues.

00:22:12.315 –> 00:22:36.240
That could then equip them equipped with that knowledge then, they could have those prioritization discussions with market access counterparts and make sure that they understand or they’re agreeing on what are the key critical evidence needs, in what order they need to be generated, and set then a plan in terms of what results will be available when.

00:22:36.620 –> 00:22:40.585
In some countries, let’s say it’s easy to determine what you need.

00:22:41.285 –> 00:22:44.105
So in Germany, for example, it’s sort of predictable.

00:22:44.245 –> 00:22:45.605
You can write a full plan.

00:22:45.605 –> 00:22:47.145
You execute the full plan.

00:22:48.405 –> 00:22:49.445
That’s probably fine.

00:22:49.445 –> 00:22:50.325
It’s a big plan.

00:22:50.325 –> 00:22:51.285
So Right.

00:22:51.285 –> 00:22:52.085
A big plan.

00:22:52.085 –> 00:22:54.490
But it’s kind of it’s deterministic.

00:22:54.710 –> 00:22:58.570
You can determine it sort of upfront and get it done.

00:22:58.710 –> 00:23:07.385
With most other countries, let’s say there’s a cool bit that, you know, you need and there’s probably 80 of it that you may need.

00:23:07.765 –> 00:23:12.425
And maybe then some of that 80% is things that you would need reactively.

00:23:13.045 –> 00:23:22.340
But I think because in market access, people have been burned so many times that it takes so long to generate evidence that they ask for everything upfront.

00:23:22.480 –> 00:23:22.960
Everything.

00:23:22.960 –> 00:23:24.240
Absolutely everything they might need.

00:23:24.240 –> 00:23:25.360
And and that’s the challenge.

00:23:25.360 –> 00:23:37.515
And that’s why the understanding of HTA process is really important because the statistician needs to know that for example, for an Australian submission, you have a few business days turnaround for a request.

00:23:37.655 –> 00:23:37.815
Yeah.

00:23:37.815 –> 00:23:43.975
So when a question comes from PBAC, the stats needs to be done in one business day.

00:23:43.975 –> 00:23:49.950
And even if if the team is based in Europe or US, you lose already a business day from the time difference.

00:23:49.950 –> 00:23:50.270
Yeah.

00:23:50.270 –> 00:23:52.350
So it really has to be done within a business day.

00:23:52.350 –> 00:23:54.750
So to know that, they need to be ready for that.

00:23:54.750 –> 00:23:57.230
And equally, Mark Access needs to communicate the timeline.

00:23:57.230 –> 00:24:01.730
But if they don’t know that this could be the case, they don’t have that conversation.

00:24:02.110 –> 00:24:05.395
Mark Access doesn’t want everything in a plan at once.

00:24:05.395 –> 00:24:07.255
They don’t wanna wait nine months for everything.

00:24:07.475 –> 00:24:10.995
But maybe you can negotiate and say, okay, I’ll do this bit in a month.

00:24:10.995 –> 00:24:11.315
Right?

00:24:11.315 –> 00:24:14.615
These 50 tables we can do in a month.

00:24:14.675 –> 00:24:19.760
And then maybe six months later, you can have this bit, and then three months after, you can have that bit.

00:24:19.760 –> 00:24:22.160
And then they can do the planning on their side.

00:24:22.160 –> 00:24:22.320
Right?

00:24:22.320 –> 00:24:29.280
Let’s say to there’s some evidence that you need to be able to finalize the strategy, let’s say.

00:24:29.280 –> 00:24:32.865
And you need that as soon as possible because you wanna finalize the strategy.

00:24:33.245 –> 00:24:36.305
A lot of the things are just things that need to be in a dossier.

00:24:36.365 –> 00:24:40.685
It’s not influencing that your decisions in terms of your strategy.

00:24:40.685 –> 00:24:44.045
It’s not influencing the outcome of the submission, but it has to be there.

00:24:44.045 –> 00:24:45.085
Safety, for example.

00:24:45.085 –> 00:24:45.420
Right?

00:24:45.500 –> 00:24:46.860
You need safety in your submission.

00:24:46.860 –> 00:24:52.460
You have to describe the safety, but it’s just tables that need to be there essentially because you already know the safety profile of the drug.

00:24:52.460 –> 00:24:54.800
That’s not changing because you’re doing additional analysis.

00:24:55.100 –> 00:25:00.735
It’s just you maybe need it in the format that is required by your agency, and therefore, it needs to be done.

00:25:00.815 –> 00:25:07.875
But if you don’t have that knowledge, then you’re just churning these tables without an understanding of why you’re doing them.

00:25:08.335 –> 00:25:11.375
And that is a very bad situation to be in.

00:25:11.375 –> 00:25:11.695
Yeah.

00:25:11.695 –> 00:25:11.935
Yes.

00:25:11.935 –> 00:25:19.600
If you don’t understand why you’re doing them and what is actually leeway of discussing about it.

00:25:19.600 –> 00:25:22.560
So typical discussions that, for example, could come up.

00:25:22.560 –> 00:25:24.980
Why do we need to do all these subgroup analysis?

00:25:25.360 –> 00:25:30.170
Well, because you have specified these subgroups and these endpoints in your protocol.

00:25:30.170 –> 00:25:39.275
And Therefore, by design and by requirement in Germany, you will need to submit these subgroup analysis.

00:25:39.895 –> 00:25:42.475
You can’t negotiate about these certain things.

00:25:42.695 –> 00:25:50.100
And you can have an opinion about how stupid or not stupid it is, but that opinion will not change the requirement.

00:25:51.280 –> 00:25:57.540
So certain things are just the way it is and the understanding that there’s no kind of discussion about certain things.

00:25:57.760 –> 00:26:00.495
However, there’s of course discussion about other things.

00:26:01.055 –> 00:26:06.515
And having an understanding about this is really important also for the design of the study.

00:26:06.815 –> 00:26:08.755
For what do you write in your protocol?

00:26:09.215 –> 00:26:12.835
When do you collect, for example, certain endpoints?

00:26:13.295 –> 00:26:21.320
I’ve seen that people miss to collect EQ5D at various other endpoints across the study.

00:26:21.620 –> 00:26:27.795
And because they thought, that’s too too much of a burden, so we cut it out.

00:26:28.035 –> 00:26:28.275
Yeah.

00:26:28.275 –> 00:26:32.055
It doesn’t seem to be relevant, given that’s just five questions.

00:26:32.435 –> 00:26:33.875
So, can’t be that relevant?

00:26:33.875 –> 00:26:34.915
Let’s kick it out.

00:26:34.915 –> 00:26:35.415
Yeah.

00:26:35.715 –> 00:26:36.775
Protocol simplification.

00:26:37.555 –> 00:26:41.370
And then, you know, people don’t see what is the impact of that.

00:26:41.530 –> 00:26:50.410
And years later, when the data readout comes and the questions from the market access people come, you’re just getting like, oh, we haven’t recorded it.

00:26:50.410 –> 00:26:53.630
And that’s a really, really difficult situation to be in.

00:26:53.915 –> 00:26:53.995
Yeah.

00:26:53.995 –> 00:27:00.155
And I’m hoping that, obviously, you know, mark access teams are involved in these designs, but actually, yeah, it would help as well.

00:27:00.155 –> 00:27:13.670
And, you know, for example, in France, if you want reimbursement in a particular subgroup, or if the plan is to get reimbursement only in a subgroup of the label population, You need the subgroup to be in your hierarchy per protocol.

00:27:13.730 –> 00:27:15.250
It has to be a formal subgroup.

00:27:15.250 –> 00:27:16.530
You have to do a test.

00:27:16.530 –> 00:27:18.470
You have to show significance in that subgroup.

00:27:18.930 –> 00:27:21.735
And and that has major protocol implications, for example.

00:27:21.975 –> 00:27:23.495
There are limited examples of that.

00:27:23.495 –> 00:27:26.395
The endpoint one is probably like a more common thing that happens.

00:27:26.535 –> 00:27:35.115
Obviously, having that understanding helps not only the HTA statisticians, right, but also the ones who are, you know, responsible for the design of the trial.

00:27:35.560 –> 00:27:44.120
And, you know, there will always be a push from different functions for different things, endpoints, or to simplify or to, you know, reduce the burden for the patient.

00:27:44.120 –> 00:27:48.700
And you need to make sure that kind of all of the right parties are involved in making those decisions.

00:27:48.840 –> 00:27:49.340
Right?

00:27:49.880 –> 00:27:50.380
Yep.

00:27:51.295 –> 00:28:02.415
Maybe maybe another thing that would help as well that having that education is I think, you know, statisticians can take kind of a much more active role in educating other functions as well.

00:28:02.415 –> 00:28:04.355
So, like, for example, Mark Access colleagues.

00:28:04.710 –> 00:28:13.350
So in in one of the previous companies I worked at, some of the work would be outsourced to a CRO and there’d be a specific cost to, like, a per table cost.

00:28:13.350 –> 00:28:13.850
Right?

00:28:13.910 –> 00:28:27.605
So the first thing I would do when I receive the request from an affiliate, for example, 700 tables, the first thing I would tell them is you realize this will cost the company 7, you know, whatever, how many hundred times that that price.

00:28:27.605 –> 00:28:30.260
And then they’ll think, oh, I didn’t know that.

00:28:30.260 –> 00:28:31.300
That’s a lot of money.

00:28:31.300 –> 00:28:32.740
Maybe we’ll take out some stuff.

00:28:32.740 –> 00:28:34.520
We don’t really need this stuff actually.

00:28:34.820 –> 00:28:39.940
And just even that something simple like that kind of is immediately people prioritize immediately after that.

00:28:39.940 –> 00:28:45.935
Because again, in many countries, you’re sure about some things, but most of the things you’re not a % sure about.

00:28:46.235 –> 00:29:02.080
And getting them to focus on what they’re sure about, but making sure you have processes in place to quickly generate the things that they might need on short notice is kind of critical to avoiding the massive workload and unnecessary work at the end of the day.

00:29:02.080 –> 00:29:05.700
Without those quick turnaround processes in place, this wouldn’t work.

00:29:05.760 –> 00:29:06.000
Right?

00:29:06.000 –> 00:29:08.900
And you’d be back in the place where they’ll say, well, you know what?

00:29:08.960 –> 00:29:14.015
We can’t wait two weeks to have the results of an urgent request, so we just want everything upfront.

00:29:14.015 –> 00:29:14.175
Right?

00:29:14.175 –> 00:29:16.115
And then it’s very difficult to then negotiate.

00:29:17.375 –> 00:29:24.595
I highly recommend that you have dedicated statisticians that work on nothing but said.

00:29:25.130 –> 00:29:34.190
To be realistic, Craig Mallebrad once said to me, if you’re working regulatory and something else, this something else will just not happen.

00:29:34.730 –> 00:29:37.470
When push comes to shove, it will not happen.

00:29:37.625 –> 00:29:37.945
Yeah.

00:29:37.945 –> 00:29:39.165
It will always lose.

00:29:39.305 –> 00:29:59.990
So having some ring fenced, both programming and statistics resources that can kind of prioritize these kind of requests will make a huge difference and can decrease the overall burden because you can ensure the local affiliates that they will get what they need if they really need it.

00:30:00.050 –> 00:30:00.550
Mhmm.

00:30:00.610 –> 00:30:04.070
It definitely helps, and that’s where the planning is important as well.

00:30:04.285 –> 00:30:14.765
Because also sometimes I do realize I mean, I have experience, for example, even if there’s a dedicated team, sometimes they’re like brought in to help with regulatory anyway, some other products.

00:30:14.765 –> 00:30:21.930
So I think, yeah, the the most important aspect is just having dedicated people, but also being very clear about when you will need help.

00:30:21.930 –> 00:30:22.250
Right?

00:30:22.250 –> 00:30:26.030
Because some countries very predictable when you’re gonna get questions.

00:30:26.330 –> 00:30:29.075
So, you know, this date is when I’m getting questions.

00:30:29.075 –> 00:30:33.155
So you need to block the five days after that to do all the analysis that are needed.

00:30:33.155 –> 00:30:33.635
Yeah.

00:30:33.635 –> 00:30:34.435
Some is like this.

00:30:34.435 –> 00:30:35.795
Some you don’t know when you get it.

00:30:35.795 –> 00:30:39.155
But there’s a lot of the work that you can preplan and kind of yes.

00:30:39.155 –> 00:30:39.655
Exactly.

00:30:40.035 –> 00:30:43.955
Ring fence the resource that you will need because you know when you’re gonna need it.

00:30:43.955 –> 00:30:44.310
Right?

00:30:44.470 –> 00:30:46.390
But, you know, a lot of it is also the processes.

00:30:46.390 –> 00:30:46.630
Right?

00:30:46.630 –> 00:30:54.950
And I think we can’t forget processes because if you need to turn something around in twenty four hours, you can’t have a three day approval period.

00:30:54.950 –> 00:30:55.450
Right?

00:30:55.670 –> 00:30:55.830
So

00:30:56.070 –> 00:30:56.570
Yes.

00:30:56.710 –> 00:31:06.605
And that’s maybe more the onus of the mark access team is to make sure when you get this request that the people who approve are there as well because you need the approval immediately.

00:31:06.745 –> 00:31:17.750
So you need to make sure that everyone is sitting at a table, a virtual table, and that we’re going through the request and that it’s immediately approved on that call and that this can begin work immediate.

00:31:18.050 –> 00:31:22.310
Again, this is where process is very important.

00:31:22.370 –> 00:31:23.910
Understanding process is important.

00:31:23.970 –> 00:31:29.595
A lot of the pieces of the education on the market access side is if they know the process, they know who to involve.

00:31:30.055 –> 00:31:41.400
They also need to explain to the people approving that you need to approve it immediately because, like, if you don’t agree, you have to conversation right now, right here because then we need to figure out a plan b, but, you know, you need to be there.

00:31:41.400 –> 00:31:42.920
So that’s kind of really important as well.

00:31:42.920 –> 00:31:49.240
And, you know, even beyond that, I’d say another like, the upcoming challenge now and, you know, some some companies are living it right now.

00:31:49.240 –> 00:31:50.040
It’s JCA.

00:31:50.040 –> 00:31:52.540
You didn’t mention JCA, but the joint clinical assessment.

00:31:52.600 –> 00:31:53.740
I won’t use an acronym.

00:31:54.360 –> 00:31:54.860
Yeah.

00:31:55.605 –> 00:32:00.405
For the joint clinical assessment is a new kind of as if it wasn’t complicated already.

00:32:00.405 –> 00:32:09.060
This is the consolidation of, let’s say, the clinical evaluation of new treatments from a health technology assessment perspective.

00:32:09.060 –> 00:32:09.460
Right.

00:32:09.460 –> 00:32:12.360
A European, consolidated assessment.

00:32:12.500 –> 00:32:20.920
So the idea is that, right, your regulatory assessment is assessing the efficacy and safety of your product and making decisions on that benefit risk profile.

00:32:21.485 –> 00:32:31.085
What is done in the joint clinical assessment is now understanding how this new treatment is changing the therapeutic context in that disease.

00:32:31.085 –> 00:32:31.325
Right?

00:32:31.325 –> 00:32:39.560
So they’re interested in looking at, yes, again, the your safety and efficacy data but maybe more like in comparison to what’s already available.

00:32:39.860 –> 00:32:44.280
So it’s things like indirect treatment comparisons, these kinds of things you will need in your dossier.

00:32:44.820 –> 00:32:52.360
But the major complication with this for statisticians is the timeline aspect and the amount of work aspect.

00:32:53.035 –> 00:33:09.880
And even with ring fenced resources with quick processes, I think it would be very difficult to get everything done on time without thinking much more broader than that in terms of how you are more efficient.

00:33:10.500 –> 00:33:26.415
Things like automation, programs already set in place, thinking a little bit outside the box of how things are done normally because I don’t wanna go too much in detail on the process, but, essentially by the time you’re locked into what you know you need to do for the dossier.

00:33:26.415 –> 00:33:31.635
So there’s something called a PICO, which is patient intervention comparator outcomes.

00:33:32.095 –> 00:33:38.760
The initial stage of the process of the JCA dossier is to define all the picos that are relevant for the European area.

00:33:38.820 –> 00:33:39.320
Right?

00:33:39.380 –> 00:33:42.600
So you may have one, five, 10, 20 picos in the end.

00:33:42.900 –> 00:33:49.000
But from that point onwards where the picos are set, you have less than a hundred days to submit a dossier.

00:33:49.515 –> 00:33:55.835
And, you know, if you’re working in a cross functional team that is preparing a dossier, they want the stats analysis Yep.

00:33:56.155 –> 00:33:56.635
Today.

00:33:56.635 –> 00:34:02.235
The day that they want it immediately because that’s delay because they need as much time as possible to write the dossier.

00:34:02.235 –> 00:34:02.670
Right?

00:34:02.830 –> 00:34:09.250
And to prepare and to finalize the dossier and for it to go through review all of this stuff, a hundred days is not a very long time at all.

00:34:09.390 –> 00:34:17.490
So with this, you need to think very, very carefully, not just resource but also all of the operational aspects surrounding the resource.

00:34:17.895 –> 00:34:40.110
And, again, think about templates, processes, programming, automation, you know, all of the identifying all the possible bottlenecks that you might have and trying to figure out how you avoid them, these kinds of things, because otherwise, you know, in an environment where you want things immediately, any delay is is too much.

00:34:40.110 –> 00:34:40.610
Right?

00:34:40.830 –> 00:34:43.950
You’re you’re gonna frustrate the the the the other members of the team.

00:34:43.950 –> 00:34:47.305
So I think it’s very important to, think about that.

00:34:47.305 –> 00:34:55.325
You you need you’ll need the dedicated people definitely, but even with dedicated people, when you think about potentially having to do thousands of tables

00:34:55.785 –> 00:34:57.805
And I can share a story about that.

00:34:57.865 –> 00:35:00.205
We submitted a dossier to Germany.

00:35:00.740 –> 00:35:07.240
And for one of the studies that we are analyzing, they pushed back on the overall population that we analyzed.

00:35:07.860 –> 00:35:17.735
And so, basically, with this pushback on the population, they said, well, for the studies, there’s no evidence because all the tables were based on that population.

00:35:17.955 –> 00:35:18.435
Yeah.

00:35:18.435 –> 00:35:23.095
And so no evidence there would have had a major impact in the price.

00:35:23.635 –> 00:35:34.110
And within the German process, you have, after you know that, three weeks, real weeks, not working weeks, you have three weeks to respond.

00:35:34.730 –> 00:35:56.025
But because we knew that this could happen, we had set up all our systems and processes so that we had more than 12,000 tables reproduced, checked against the original tables so that we can see what were the differences within three days.

00:35:56.245 –> 00:36:08.490
So we had the rest more than two weeks to actually then write the dossier, and we more or less submitted a completely new dossier, which kind of surprised the HDA body.

00:36:08.490 –> 00:36:13.305
But, because they had very, very little time to review everything.

00:36:13.785 –> 00:36:16.525
But this is how we saved that submission.

00:36:17.225 –> 00:36:26.205
And in the similar way for JCA, you also need to have systems in place so that you can react really, really fast.

00:36:26.820 –> 00:36:27.320
Yes.

00:36:27.540 –> 00:36:29.160
So preparation is key.

00:36:29.300 –> 00:36:31.460
And in this case, right, preparation was key.

00:36:31.460 –> 00:36:38.820
And you need to think about all of this upfront because exactly that in in your situation, if the preparation hadn’t been done, it would have been impossible.

00:36:38.820 –> 00:36:38.980
Right?

00:36:38.980 –> 00:36:39.300
Yep.

00:36:39.620 –> 00:36:40.100
Even with

00:36:40.420 –> 00:36:41.300
All hands on deck.

00:36:41.300 –> 00:36:41.800
Yeah.

00:36:42.075 –> 00:36:43.215
No no problem.

00:36:43.355 –> 00:36:43.835
Yeah.

00:36:43.835 –> 00:36:45.675
Well, hands on deck, you wouldn’t be able to do it.

00:36:45.675 –> 00:36:49.915
And I think that’s really important because, you know, often systems are not set up to do that.

00:36:49.915 –> 00:36:50.315
Right?

00:36:50.315 –> 00:36:53.915
You need to proactively prepare this kind of thing.

00:36:53.915 –> 00:36:57.030
And, you know, with JCA, it’s going to be by 2028.

00:36:57.030 –> 00:37:03.030
Most submissions will have the JCA be a reality for everyone for for every every asset.

00:37:03.030 –> 00:37:08.150
So Currently only affects oncology, but the other areas will come as well.

00:37:08.150 –> 00:37:09.370
Oncology and AMTPs.

00:37:09.430 –> 00:37:09.750
Yeah.

00:37:09.750 –> 00:37:25.620
One other tactic that I have seen being really helpful is my European PRI counterpart organized a meeting where she invited all the local architects as people into one place at one time.

00:37:27.200 –> 00:37:32.100
And every MarketAxess team needed to present what they wanted.

00:37:32.240 –> 00:37:41.165
And that helped to understand, you know, mutual how things were overlapping, where were actually differences.

00:37:42.025 –> 00:37:57.770
And it also forced the market access people to really think upfront what they really need, which is sometimes actually a challenge because it could be that your local market access people are staffed quite late in the process.

00:37:58.230 –> 00:38:03.370
By the time you want to talk to them, maybe they don’t have someone in the seat at the office.

00:38:03.545 –> 00:38:11.405
So that can be another kind of challenge with staff turnover or staff not, not being in, assigned yet.

00:38:12.105 –> 00:38:12.425
Yes.

00:38:12.425 –> 00:38:13.465
That’s very useful.

00:38:13.465 –> 00:38:41.495
And, you know, I think if you are a kind of medium sized company, at least you should think about things like having kind of statistical analysis plans dedicated to HTA and these kinds of things where you would formalize this this process of engaging with countries via your mark access counterparts and consolidating all of the requests into a plan and also having the prioritization of that plan as well within that.

00:38:41.495 –> 00:38:41.655
Right?

00:38:41.655 –> 00:38:45.435
So I think, again, with with this kind of thing as well, you have to be flexible.

00:38:47.490 –> 00:38:50.630
You know, I think when statisticians thinks of an SAP, they think I have to do everything in that SAP.

00:38:50.690 –> 00:38:51.190
Right?

00:38:51.970 –> 00:38:55.350
There’s a plan and everything needs to be done that’s on there that’s prespecified.

00:38:56.370 –> 00:39:02.165
But that’s why HTA is a bit different because some of the things, you know, you need, some of the things you don’t.

00:39:02.165 –> 00:39:05.205
So why should you do things that you don’t necessarily need?

00:39:05.205 –> 00:39:05.445
Right?

00:39:05.445 –> 00:39:21.250
And I think sometimes that requires a shift in the way processes are defined or shift in the way people think about things and a new SOP, for example, just for the HTA part where it’s clearly defined that certain things are only done if needed, for example.

00:39:21.250 –> 00:39:21.410
Right?

00:39:21.410 –> 00:39:28.070
These are the flexibilities that you need to introduce to avoid being inefficient and avoid doing things unnecessarily in organization.

00:39:28.795 –> 00:39:29.035
Yeah.

00:39:29.035 –> 00:39:35.375
And these kind of process changes, let’s be realistic, can take quite a time.

00:39:35.515 –> 00:39:36.015
Mhmm.

00:39:36.395 –> 00:39:40.175
So that’s why you also need to work early on it.

00:39:40.795 –> 00:39:44.680
Now, of course, there’s one other thing you can do.

00:39:44.820 –> 00:39:48.280
You could just ask Neshedd to help you with things.

00:39:50.180 –> 00:39:54.600
Neshedd, how could you help, companies improve these things?

00:39:54.965 –> 00:40:06.325
As a company, we we really try and focus on being a bridge between kind of how a strategy is defined and then how that strategy is kind of executed down the line.

00:40:06.325 –> 00:40:06.645
Right?

00:40:06.645 –> 00:40:21.900
So global vision, local strategy, or thinking about then thinking about how to take things locally and put it into some kind of global structure or global plan with specifically in terms of how we can help kind of stats organizations.

00:40:22.925 –> 00:40:24.765
We can offer things like the training.

00:40:24.765 –> 00:40:25.005
Right.

00:40:25.005 –> 00:40:29.585
So I talked a lot about, mutual understanding, kind of foundational knowledge.

00:40:30.045 –> 00:41:11.510
So that’s something that we do thinking about HTA one zero one for for statisticians and really focusing on what does a statistician need to know about, reimbursement, pricing, market access, etcetera, so that they can be more effective in how they work and so that they’re equipped with the knowledge and tools to be able to have those critical conversations with market access eye to eye and be able to ask the right questions and ensure that they’re getting the right information so that then they can work with Mark Access to really ensure that, you know, everyone is getting what they need when they need it and that people aren’t doing work unnecessarily or aren’t working on things when they’re not needed.

00:41:11.510 –> 00:41:28.055
You know, conversely, the the same way around for mock access, you know, your HR functions, etcetera, giving them the understanding a little bit of how stats works and how processes work would then help them also understand how they can communicate better with statistics.

00:41:28.055 –> 00:41:28.375
Right?

00:41:28.375 –> 00:41:36.395
But I think statisticians, if they have the understanding, they can have the active role asking the right questions, and that’s why the foundational training is very important.

00:41:37.470 –> 00:41:45.170
Another thing that we do is with the well, HTA in general, but specifically really the the JCA prep.

00:41:45.310 –> 00:41:49.090
So kind of thinking about organizational readiness for JCA.

00:41:49.310 –> 00:41:55.605
We talked a lot about processes, automation, bottlenecks, you know, all of this stuff.

00:41:55.665 –> 00:42:13.860
But really thinking kind of thinking very comprehensively about how is the organization set up and how does it need to change to be able to overcome the different challenges of having to do JCA at the same time as regulatory submissions?

00:42:13.920 –> 00:42:16.500
Do they need to rethink how the teams are structured?

00:42:16.800 –> 00:42:21.380
Do they need to address policies, standard operating procedures?

00:42:21.520 –> 00:42:31.485
Do they need to think about different ways of doing things, templates, programming code, how approval processes work, automation of things, all of these things.

00:42:31.545 –> 00:42:44.180
And, you know, every company will kind of address it in a different way, but really going through that assessment and decision making around how the organization needs to evolve, that’s something that we can support with as well.

00:42:44.480 –> 00:42:52.545
And then, of course, we can support with all of those changes, whether it’s new programs, new tools, new frameworks, these kinds of things.

00:42:52.845 –> 00:42:58.065
Being a kind of technically focused consultancy, it’s something that we can support with as well.

00:42:59.245 –> 00:42:59.745
Awesome.

00:43:00.125 –> 00:43:16.155
Thanks, Neshdette, for this amazing discussion about statistics and market access, how they can work effectively together, because I think that making that relationship effective takes out so much pain of the process.

00:43:17.035 –> 00:43:19.435
And so I’ve seen both sides.

00:43:19.435 –> 00:43:25.295
I’ve seen very painful collaborations and I’ve seen very very smooth collaborations.

00:43:25.595 –> 00:43:29.375
And you really wanna work on Zolata, on Zolata.

00:43:29.595 –> 00:43:31.050
I can’t guarantee you.

00:43:31.530 –> 00:43:32.670
Thanks so much, Nashtad.

00:43:33.130 –> 00:43:34.730
And thank you very much for inviting me.

00:43:34.730 –> 00:43:37.070
It’s been a pleasure after so many years.

00:43:37.370 –> 00:43:38.910
I look forward to the next one.

00:43:39.530 –> 00:43:41.470
Probably sooner rather than later.

00:43:41.930 –> 00:43:42.410
Alright.

00:43:42.410 –> 00:43:42.890
Thank you.

00:43:42.890 –> 00:43:43.870
Thank you, Alexander.

00:50:22.570 –> 00:50:26.190
This show was created in association with, PSI.

00:50:26.570 –> 00:50:32.110
Thanks to Reine and her team at VVS who helped with the show in the background, and thank you for listening.

00:50:32.570 –> 00:50:35.790
Reach your potential, lead great science, and serve patients.

00:50:36.385 –> 00:50:38.805
Just be an effective statistician.