We extracted populations from the WHO database for each country, the NAFLD prevalence of each country is extracted from the last publications, and when the value is not known, we apply the regional rate, or the closest country rate.
The NASH rate in NAFLD patients used is the one presented at the last NASH TAG conference 2018 in UTAH (20%), the previous published was higher (24%).
The F0 to F4 rates in NASH patients population are extracted from the same presentation.
Each drug candidate is qualified regarding the publications and get notations on :
▪ Stage of fibrosis targeted ( from F0 to F4).
A note is also given on other pathologies interactions and potential restrictions
▪ Cardio Vascular Risk Patients.
▪ Diabetic Patients.
This allow to include in the forecast potential use restrictions and segment the market of each drug.
When data’s on adverse effect are not known, we assume that there is no potential restrictions of drug use. It can change as soon new data’s are published.
Potential drug agreement date is estimated regarding:
▪ Clinical trial advancement.
▪ Drug status (Fast Track, Breakthrough therapy or potential Subpart H)
We also suppose that only a little part of patients under prescription change their drug each year. The rate is different from one drug to the other because of the adverse effects.
We give a compliance note to each drug as a percentage of prescriptions reiterated from year to year ( example, 90% mean that the drug lost 10% of patients under prescription each year).
Those data’s are updated as soon news are published !
BACKBONE OR COMPLEMENTARY TREATMENTS
Discussing with labs and KOLs it appear clear now that the future of NASH treatment will rely on combinations of drugs.
It is to early to talk of packaged combos, because they will need more clinical trials to evaluate the doses ratios valuable for the majority of patients and it will take time.
What we are talking about is combinations of prescriptions.
The most admitted scheme of future NASH treatment is the combination of a backbone treatment targeting the metabolic causes of NASH and, if possible, the co-morbidities of the disease ( T2D, hyperlipidemia, etc …), and a complementary treatment targeting fibrosis at start.
Patients with mild fibrosis (F1 and maybe F2) could be treated with the backbone treatment only, most advanced fibrosis like F3 and F4 ( compensated cirrhosis) could be completed with a drug targeting specifically hepatic fibrosis.
As more as the 'backbone treatment' will reduce inflammation and stop the fibrogenesis, the complementing treatment would be reduced, after a certain time ( maybe 1 or 2 years), only the 'backbone treatment' will be maintained, maybe for the rest of the life of patients.
The average age of NASH patients is close to 55 years. It means that the 'backbone treatment' could be prescribed for an average duration of 20 years.
On the other hand, anti-fibrotic complementary treatments could be prescribed for an average duration of 2 years.
It means, that a 'backbone treatment' should present a perfect safety, and more than that, no adverse effects reducing the patient compliance to the treatment, when dedicated anti-fibrotic treatment can support some small adverse effects.
Economy of health principles show that treatments supposed to be prescribed as backbone treatment and for lifetime need to have a low cost. At the opposite, short duration treatments can be more expensive.
Those points explain the quarrels supported by labs on the NASH treatments strategy.(you can read an article related here).
Each drug is tagged regarding the following criteria’s, allowing it to obtain the potential, 'backbone treatment' label :
▪ Targeting metabolic causes of NASH (not targeting advanced fibrosis only )
▪ A perfect safety as known to date.
▪ No aggravation of co-morbidities as CV risk or T2D
▪ No adverse effects which could reduce the patients compliance to the treatment.
▪ If possible, positive action on glycaemia and lipidemia.
The other drugs are classed as complementary treatment, mainly targeting fibrosis.
HOW THE FIGURES ARE COMPUTED
The market is divided in two big separated segments that overlap !
A first segment including only 'backbone treatments' of disease :
If they have low adverse effects, this kind of treatment compliance rate notation is quite high.
It is known that backbone treatments are rarely modified by prescriptors, if the patients compliance to the treatment is good.
So, as installed, those drugs benefit from a good market shield against new comers.
A second segment including all the other drugs, named as‘complementary drugs’
Depending of side effects, the compliance rate of those drugs is a little bit lower.
Computation and figures are computed separately for those two segments !
Market shares are computed on a large panel of patients from F1 to F4.
Average prices are not estimated very high ( from 15000 $ / year to 1000 $/ year depending of countries and type of treatment : backbone or not )
Regarding the short period of treatment, the 'complementary drugs' market would be supposed to decrease as the backbone treatments are expanding, but because of the very low diagnosis rate of the disease, we supposed that the new diagnosed patients will compensate the end of 'complementary treatment' rates.
Market shares are computed on a reduced panel of patients from F2 to F4 depending of the drug profile.
Computation is done country by country.
The principles of computation are as follows:
We divided the NASH patients into 20 groups:
2 large groups: CV risk / or not subdivided into 2 subgroups: diabetics (T2) or not, each of these 4 subgroups being distributed according to their grade of Fibrosis (0 to 5)
To help, each group is named as follows: F (grade of fibrosis) (N) C (N) D
Example: for patients with diabetes without cardiovascular risk and a fibrosis grade of 2, the group is named F2NCD. (Sometime mentioned on graphs)
Some drugs target only certain grade of fibrosis, others are poorly indicated for patients with cardiovascular risk, etc.
Using the notations already mentioned, every drug receive an individual note (0 to 1) for each group of patients.
For each of these groups, a curve is calculated month by month to simulate the maturation of the market. Its purpose is to model the progression of the knowledge of the disease and the evolution of the diagnosis rate over time.
Curbs are different for each group because it is obvious that a diabetic patient with advanced fibrosis is more likely to be diagnosed quickly than a patient with a fibrosis grade of 1, non-diabetic and without identified CV risk.
A second progressive factor is calculated month by month for all the patients, it is the progression of the rate of care related to the management of the disease, it starts from 0 and progresses linearly to reach its maximum rate in 15 years. The maximum rate of care is different for each country; it varies between 1% for a country like Sudan and 80% for Germany or France, and 70% for the USA.
It is mainly representative of the country healthcare system and insurances covering.
As explained before, NAFLD total adult patients population is calculated for each country on the basis of known and published ratios.
Based on NAFLD population, a global NASH population is estimated on the basis of the (published) average ratio of 20% of NAFLD patients.
This NASH population is then subdivided into subgroups using published ratios of diabetic rates, CV risks and each grade of fibrosis.
By multiplying the number of patients thus calculated by the first curve, group by group and then with the second curve, this time globally, one obtains, group by group and month by month the number of theoretical patient diagnosed and potentially treated.
A population growth curve unique for each country is applied to the final, month by month.
The supposed treated patients will be then distributed among drugs regarding their future estimated market share.
Initially, on each segment, every drug is compared with the other drugs to evaluate its market share and then an amount of patients is attributed to the drug. Then, for each drug, we take each month the number of patients treated on the previous month, but we remove a part of it, depending of the compliance rate.
Those‘new free' patients are added to the new diagnosed patients ofthe month as previously computed and all those new patients are dispatched to all the drugs, segment by segment.
At the end we obtain for each country, each drug, each group and each month, the estimated number of patient treated. This is a big amount of figures to compute, 100 countries x 50 drugs x 120 months x 20 groups give 12 million figures.
Once the number of patients is calculated per segment, it is summoned to obtain the total of treated patient of all groups, per month, by country, and by drug.
Then, the estimated treatment cost is fixed drug-by-drug and country-by-country
However it would be too simple to have a fixed price, so we evaluate month-by-month the number of drugs present on the market of each country.
To simulate competition impact on prices, when more than 4 drugs are present on the same segment, a discount rate is progressivelyapplied to every drug prices in the country (to date, maximum discount is arbitrary limited to 35%).
Then, month-by-month, the price of each drug is multiplied with the previously calculated patients number of each drug, which gives us a forecast income, month-by-month, which is then presented by quarter or by year according to charts!
This publication reflects the views only of the authors, and he cannot be held responsible for any use which may be made of the information contained therein. The authors of the articles published here are not physician, financial analysts or market professionals. announced data may contain errors, inaccuracies and misinterpretations of facts.The authors could have their own stoks positions on these values. it is therefore recommended to the reader to verify the facts, to inform himself before any investment on listed companies and to make decisions based on his own judgment. The informations and reflections that can be found on this website are by no means of incentives for the purchase or sale of listed securities but personal opinions of the authors, which does not represent the point of view of the mentionned companies .
Positions of G.Divry on the biotech’s mentioned :
GENFIT : H1 2013 - to date: Long
CONATUS : to date: No Position
GALT : Jan 2018 - to date: Long
MDGL : to date : No Position
ICPT : to date : No Position
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