Prof. Antonio Pellicer

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1 Improving outcomes in ART : Time-lapse technology for monitoring COS and blastocyst culture Prof. Antonio Pellicer Instituto Valenciano de Infertilidad (IVI) University of Valencia apellicer@ivi.es

- IVI is a minor shareholder in Auxogyn Co.

2 DISCLOSURE - Invitation by an unrestricted Educational Grant from COMTECMED to ASRM - IVI is a minor shareholder in Unisense Fertilitech A/S. - IVI is a minor shareholder in Auxogyn Co. - This work has not received any financial support from any commercial entity and the instrumentation, disposables and utensils belong to IVI.

3 HUMAN EMBRYONIC IMPLANTATION Health embryo at blastocyst stage - To select the best embryo/s MOLECULAR DIALOGUE Adequate Endometrial Receptivity

Improvement of ART outcomes Personalized Embryo Transfer (pet) Identification/Modification of receptive endometrium Identification of the viable embryo Window of

4 Improvement of ART outcomes Personalized Embryo Transfer (pet) Identification/Modification of receptive endometrium Identification of the viable embryo Window of Implantation Endometrial receptivity assay (ERA) Other non-invasive methods Invasive methods: CCS (D3 or D5) Non-invasive methods: Morphology Time-lapse Proteomics Metabolomics

5 Improvement of ART outcomes Personalized Embryo Transfer (pet) Identification of the viable embryo Repeated implantation failure (RIF) Aged patients Reduced ovarian reserve Endometriosis Severe male factor Recurrent miscarriage

6 Improvement of ART outcomes Personalized Embryo Transfer (pet) Identification of the viable embryo Time-lapse Invasive methods: CCS (D3 or D5).in ALL ART CYCLES?

7 Time-Lapse Technology Time-Lapse Imaging - Blastomere Activity

8 Time-Lapse Development cc2= t3-t2 count Regular divisions Viable 8 cell Viable blastocyst Implanted CC Time post insemination, hours t Regular divisions Viable 8 cell Viable blastocyst Implanted t5 count PÁG Time post insemination, hours

9 Predictive ability of embryo implantation Best correlation with implantation success PÁG.9

10 Incidence rate of direct division 1-3 in all embryos deviding to 3 cells 4510, 86% 715, 14% Direct division 1-3 cells No direct division 1-3 cells 30 *P< * 28,7% Implantation Rate ,9 % 0 DC 1-3 Not DC1-3 PÁG.10 Rubio et al. Fertil Steril 2012; 98(6)

11 Morphology ok Exclusion Criteria Direct Cleavage Uneven Blastomere non viable included 48-56h excluded T5 yes 35-40h no 35-40h T3 T3 yes no yes no Grade A Grade B Grade C Grade D Grade E Discarded CC2 5-12h CC2 5-12h CC2 5-12h CC2 5-12h yes no yes no yes no yes no A + G.11A B + B C + C D + D PÁG.11

12 Time-Lapse: Initial findings Embryo morphology correlates with embryo classification by time-lapse Embryo quality and implantation correlate with embryo classification by time-lapse In a retrospective study, time-lapse (n=1372 cycles) as compared to conventional incubators (n=5872 cycles): reduced significantly (2.8% vs 5.2%) cycle cancellation rates Increased significantly (59.1 vs 50%) ongoing pregnancy rates PÁG.12 Meseguer et al. Fertil Steril 2012; 98:1481-9

13 Randomized Controlled Trial PÁG.13 Rubio I. et al. Fertil Steril 2014; 102:

14 Inclusion Criteria ICSI MII 6 Age Previous Cycles 2 BMI Basal FSH <12 AMH >7 pmol/l Exclusion Uterine Pathologies Hydrosalpinx Recurrent Miscarriage Endometriosis PÁG.14 < 1 mill progressive sperm (A+B)

Not meeting inclusion criteria (n=22) No embryoslides available, n=8 IVF as fertilization

(n=52) Patient request TMS, n=30 IVF as fertilization procedure, n=14.

group Allocated to intervention(n=412) Received allocated to intervention (n=412)

15 Not meeting inclusion criteria (n=22) No embryoslides available, n=8 IVF as fertilization procedure, n=5. Testicular Sperm or Cripto, n=5. Already randomized, n=1. Low respond, n=3. Assessed for eligilibility (n=930) Randomized (n=856) Not meeting inclusion criteria (n=52) Patient request TMS, n=30 IVF as fertilization procedure, n=14. Testicular sperm or cripto, n=5. Already randomized, n=1. Advanced maternal age, n=1. Low respond, n=1. TMS group Allocated to intervention(n=444) Received allocated to intervention (n=444) SI group Allocated to intervention(n=412) Received allocated to intervention (n=412) Follow-up (n=444) Follow-up (n=412) Analyzed (n=438) Excluded (n=6) Cancelled donation, n=2. Embryo vitrified, n= 4. Analyzed (n=405) Excluded (n=7) Endometrial bleeding, n=1. Cancelled donation, n=2. Embryos vitrified, n=4. PÁG.15 Rubio I. et al. Fertil Steril 2014; 102:

16 TMS GROUP(n=438) CONTROL GROUP(n=404) p Blastocyst rate (%) NS Embryo Fragmentation (%) 7.5 ( ) 6.9 ( ) 0.06 Number of Blastomeres 6.9 ( ) 6.9 ( ) NS Optimal Embryos (D3) (%) Blastocyst rate (%) NS Optimal Blastocyst (D5) (%) Transferred embryos (per treatment) Cryopreserved embryos (per treatment) 1.86 ( ) 1.86 ( ) NS 3.9 ( ) 3.6 ( ) NS PÁG.16 Rubio I. et al. Fertil Steril 2014; 102:

17 Intention to treat All treated cycles All transfers Pregnancy (%) Positive ßHCG p = p = p = TMS (n=466) SI (n=464) 20 TMS (n=440) SI (n=405) 20 TMS (n=415) SI (n=373) Ongoing pregnancy (%) Fetal Heart Beat p = p = p = TMS (n=466) SI (n=464) 20 TMS (n=440) SI (n=405) 20 TMS (n=415) SI (n=373) PÁG.17 Rubio I. et al. Fertil Steril 2014; 102:

18 All pregnancies All transferred embryos Early pregnancy loss (%) TMS (n=271) p = SI (n=228) Implantation rate (%) p = 0.02 TMS (n= 775) SI (n=699) Early pregnancy loss: Positive ßhCG but no FHB Implantation rate: # embryo sacs / # embryos transferred PÁG.18 Rubio I. et al. Fertil Steril 2014; 102:

19 Model effect values OR p value Incubation TMS versus SI 1.41 ( ) Day of Transfer Day 5 versus Day ( ) Oocyte source Autologous versus 0.83 ( ) ns Donation Age years per year 0.99 ( ) ns PÁG.19 Rubio I. et al. Fertil Steril 2014; 102:

Incubator, we could have expected about 545 additional

20 If all of the 6000 treatments in the conventional incubator had been carried out using Time-Lapse Incubator, we could have expected about 545 additional pregnancies. PÁG.20 Rubio I. et al. Fertil Steril 2014; 102:

21 PÁG.21 Time-lapse data to predict blastocyst development

22 Time-lapse data to predict blastocyst development Embryo temporal distribution to reach blastocyst stage. PNF (h) 1stC (h) < > < >29.1 p<0.05 p<0.05 2ndC(h) PÁG < >43.4

3 24.4-26.3 >26.4 40 35 30 25 20 15 10 5 0 <25.2 25.

23 Time-lapse data to predict blastocyst development Embryo temporal distribution to reach expanded blastocyst stage. PNF (h) 1stC (h) < > < >29.2 p<0.05 p<0.05 2ndC (h) PÁG < >43.4

24 Time-lapse data to predict blastocyst development N= 872 P<0.001 PÁG.24

25 Time-lapse data to predict blastocyst development N= 396 Optimal blastocyst P<0.001 PÁG.25

26 Time-lapse data to predict blastocyst development * * PÁG.26

27 Time-lapse data to predict blastocyst development Tracks cell divisions Calculates timing intervals Blastocyst prediction 1. Automated Cell Tracking Software: Feeds timings to the classification tree Generates an automated prediction 2. Classification Tree HIGH probability to form a blastocyst if cell cycle markers are within range LOW probability to form a blastocyst if cell cycle PÁG.27 markers are outside of range

28 Eeva. HIGH LOW MEDIUM PÁG.28 P2: 9 h 20 min P2 11 h 28 min P3: 0 P3 1 h 44 min

Optimal Blastocyst Rate (%) HIGH (n=103) 77.

29 Algorithm Results Blastocyst prediction (n=840) EEVA category Blastocyst Rate (%) Optimal Blastocyst Rate (%) HIGH (n=103) MEDIUM (n=467) LOW (n=270) cc2 yes h no s2 s2 yes no yes no PÁG.29 HIgh High-Med Med-High Low

30 Algorithm Results KID (n=245 transferred embryos) Eeva Morpho EEVA category Implantation (%) HIGH (n=88) MEDIUM (n=108) LOW (n=49) cc2 yes h no s2 s2 yes no yes no HIgh High-Med Med-High Low PÁG.30

Time-lapse data to predict blastocyst development Specificity measures false positives Significantly improved in 3 out of 3 embryologists More consistent

31 Time-lapse data to predict blastocyst development Specificity measures false positives Significantly improved in 3 out of 3 embryologists More consistent embryo assessment using D3 morphology + Eeva information Conaghan et al. Fertility & Sterility (2013) # p< **p<0.001 relative to Morphology only PÁG.31

32 Time-lapse and COS N= 319 ICSI oocyte donation cycles N= 2132 embryos a-gnrh hcg an-gnrh FSH FSH

ongoing pregnancy rates and miscarriage.

33 CONCLUSIONS Personalized Medicine is the next step in ART Time-lapse is a good method of embryo selection: correlation with embryo quality, implantation, ongoing pregnancy rates and miscarriage. Time-lapse increases ongoing pregnancy rates by 10% in RCTs Time-lapse is helpful in the prediction of blastocyst development

35 Aknowledgements Marcos Meseguer Irene Rubio Carmen Rubio Daniela Galliano Manuel Munoz Carlos Simón

Here s Looking at You, Kid: Time Lapse in the Clinical Embryology Laboratory

Here s Looking at You, Kid: Time Lapse in the Clinical Embryology Laboratory Thomas B. Pool, Ph.D., HCLD Fertility Center of San Antonio San Antonio, Texas Disclosures Speaker, Auxogyn Symposium, ASRM,