Podcast
Empowered Patient Podcast
Hosted by Karen Jagoda · EN
Empowered Patient Podcast with Karen Jagoda is a window into the latest innovations in digital health, the changing dynamic between doctors and patients, and the emergence of precision medicine. The show covers such topics as aging in place, innovative uses for wearables and sensors, advances in clinical research, applied genetics, drug development, and challenges for connected health entrepreneurs.
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Patient-Centric Drug Development for Ovarian Cancer Targets Tumor Survival Pathway with Dr. Stella Vnook Kaida Biopharma TRANSCRIPT
6d agoTap to summarizeDr. Stella Vnook, Co-Founder and Executive Chair of Kaida Biopharma, highlights the advantages for an early-stage biotech company to take a patient-centric perspective in drug development. She defines patient-centricity as focusing on whether a drug meaningfully improves a patient's life, which should influence decisions about trial design, endpoints, and side effects from the earliest stages. Kaida's work on a new treatment for ovarian cancer is designed to target tumor survival mechanisms and overcome treatment resistance, and has from the beginning taken into consideration the tolerability of treatments and the patient's quality of life. Stella explains, "We're so used to thinking drug-centric, and it's true that in the early stages of development, it's all about the molecule and the mechanism of action, and it's exciting to see how it works. But we really need to be thinking patient-centric because we will make decisions differently from the start. So it's not just about whether this drug works and how, but whether it meaningfully changes a patient's life. I think that's what patient-centric is or should be, because that would impact trial design, endpoints, and how we view tolerability or combination therapy." "For ovarian cancer, women today may receive a variety of treatments. Now, let's talk about this for a second. It's the cancer that's usually diagnosed very late. That means the patient's tumor has already gone into the lymph nodes, and it's what we call a stage three PO4. The patients after surgery receive a variety of drugs such as platinum therapies or PARP, but they still may relapse, and they may become resistant to the therapy. Now, that initial therapy has probably had significant toxicity. Because they've become resistant to the therapy they received, now they have limited options. So fortunately, there are drugs that potentially could be eligible for FRA positive. There's been a lot of news about ELAHERE, which is great, but it's only 25% of the population, and many patients may never qualify for this treatment. So that's where Kaida comes in, because we're focusing on 80% of the population." "Actually, the name Kaida is a dragon that eats its own tail. So that talks about the mechanism of action we've discussed: resistance. What we do is when the treatment has been given, it supports cell survival and actually eliminates the tumor's ability to replicate, which is called proliferation, causing it to destroy itself, which is called apoptosis. So in essence, the tumor disrupts itself because we're cutting off its support system." #Kaida #OvarianCancer #PatientCentric #OncologyInnovation #ProlactinReceptor #DrugDevelopment #AIinHealthcare #RealWorldEvidence #TolerabilityMatters #KaidaBiopharma #CancerCare Kaida-biopharma.com Listen to the podcast here
Transcribe →Patient-Centric Drug Development for Ovarian Cancer Targets Tumor Survival Pathway with Dr. Stella Vnook Kaida Biopharma
6d ago00:19:27Tap to summarizeDr. Stella Vnook, Co-Founder and Executive Chair of Kaida Biopharma, highlights the advantages for an early-stage biotech company to take a patient-centric perspective in drug development. She defines patient-centricity as focusing on whether a drug meaningfully improves a patient's life, which should influence decisions about trial design, endpoints, and side effects from the earliest stages. Kaida's work on a new treatment for ovarian cancer is designed to target tumor survival mechanisms and overcome treatment resistance, and has from the beginning taken into consideration the tolerability of treatments and the patient's quality of life. Stella explains, "We're so used to thinking drug-centric, and it's true that in the early stages of development, it's all about the molecule and the mechanism of action, and it's exciting to see how it works. But we really need to be thinking patient-centric because we will make decisions differently from the start. So it's not just about whether this drug works and how, but whether it meaningfully changes a patient's life. I think that's what patient-centric is or should be, because that would impact trial design, endpoints, and how we view tolerability or combination therapy." "For ovarian cancer, women today may receive a variety of treatments. Now, let's talk about this for a second. It's the cancer that's usually diagnosed very late. That means the patient's tumor has already gone into the lymph nodes, and it's what we call a stage three PO4. The patients after surgery receive a variety of drugs such as platinum therapies or PARP, but they still may relapse, and they may become resistant to the therapy. Now, that initial therapy has probably had significant toxicity. Because they've become resistant to the therapy they received, now they have limited options. So fortunately, there are drugs that potentially could be eligible for FRA positive. There's been a lot of news about ELAHERE, which is great, but it's only 25% of the population, and many patients may never qualify for this treatment. So that's where Kaida comes in, because we're focusing on 80% of the population." "Actually, the name Kaida is a dragon that eats its own tail. So that talks about the mechanism of action we've discussed: resistance. What we do is when the treatment has been given, it supports cell survival and actually eliminates the tumor's ability to replicate, which is called proliferation, causing it to destroy itself, which is called apoptosis. So in essence, the tumor disrupts itself because we're cutting off its support system." #Kaida #OvarianCancer #PatientCentric #OncologyInnovation #ProlactinReceptor #DrugDevelopment #AIinHealthcare #RealWorldEvidence #TolerabilityMatters #KaidaBiopharma #CancerCare Kaida-biopharma.com Download the transcript here
Transcribe →Redefining Primary Care for Older Women with Dr. Deb Dittberner Herself Health TRANSCRIPT
1w agoTap to summarizeDr. Deb Dittberner, Chief Clinical Officer and Director of Population Health at Herself Health, focuses on providing value-based care for women aged 50 and older through a model that prioritizes cognition, bone health, behavioral health, and cardiac health. Conventional primary care for older women often overlooks the complexities of aging, which Herself Health addresses through longer visits, proactive screening, and patient education. Technology is being successfully integrated into the environment to provide virtual visits, support medication adherence, and improve access to care. Deb explains, "We are focusing on women 50 +, specifically women 65-plus who are heading into that Medicare world and have more complex medical problems. We see a real need to focus on that group, where we can create team-based care and deliver population health, value-based care for those patients, with a greater focus on keeping them well. And lowering healthcare costs and doctor visits by focusing on wellness rather than fee-for-service or on illness and problems." "I think that as we age, it becomes more complicated. And I think advanced primary care takes that into consideration. We do longer visits for these patients. We focus on keeping them well. And what we're trying to do is look at the whole picture. Aging people have more hypertension, more diabetes, more chronic medical conditions, and taking the time to help with all of those conditions together and look at the whole picture is what we're trying to do." #HerselfHealth #PrimaryCare #WomensHealth #ValueBasedCare #Geriatrics #HealthcareInnovation #PatientCenteredCare #MedicareAge #ClinicalLeadership #HealthEquity #AdvancedPrimaryCare #HealthTech #PopulationHealth herself-health.com Listen to the podcast here
Transcribe →Redefining Primary Care for Older Women with Dr. Deb Dittberner Herself Health
1w ago00:20:22Tap to summarizeDr. Deb Dittberner, Chief Clinical Officer and Director of Population Health at Herself Health, focuses on providing value-based care for women aged 50 and older through a model that prioritizes cognition, bone health, behavioral health, and cardiac health. Conventional primary care for older women often overlooks the complexities of aging, which Herself Health addresses through longer visits, proactive screening, and patient education. Technology is being successfully integrated into the environment to provide virtual visits, support medication adherence, and improve access to care. Deb explains, "We are focusing on women 50 +, specifically women 65-plus who are heading into that Medicare world and have more complex medical problems. We see a real need to focus on that group, where we can create team-based care and deliver population health, value-based care for those patients, with a greater focus on keeping them well. And lowering healthcare costs and doctor visits by focusing on wellness rather than fee-for-service or on illness and problems." "I think that as we age, it becomes more complicated. And I think advanced primary care takes that into consideration. We do longer visits for these patients. We focus on keeping them well. And what we're trying to do is look at the whole picture. Aging people have more hypertension, more diabetes, more chronic medical conditions, and taking the time to help with all of those conditions together and look at the whole picture is what we're trying to do." #HerselfHealth #PrimaryCare #WomensHealth #ValueBasedCare #Geriatrics #HealthcareInnovation #PatientCenteredCare #MedicareAge #ClinicalLeadership #HealthEquity #AdvancedPrimaryCare #HealthTech #PopulationHealth herself-health.com Download the transcript here
Transcribe →Using Health AI Platforms to Bridge Gaps in Patient Care with Matt Blosl DexCare TRANSCRIPT
2w agoTap to summarizeMatt Blosl, CEO of DexCare, has a core mission to help large health systems use AI responsibly to attract patients and work with them to get appropriate care. While AI's data-processing capabilities are transformative, its use in clinical recommendations remains in its early stages, constrained by fragmented data and the limited availability of validated diagnoses. Matt advises healthcare leaders to adopt a problem-first approach to AI implementation and to use technology to drive significant change rather than just incremental improvements to existing workflows. Matt explains, "Artificial intelligence is interesting. We're still in what I consider to be the Gold Rush phase of a new technology. Certainly one as disruptive as this. So I think a lot of our clients are still trying to figure out what it means. From my perspective, you said it very well. Google or the internet was kind of our first foray into providing patients more access before they even seek care or before they go in to receive care. And what I see right now is that the AI platforms are kind of the next level of that. The richness of the information is greater. And so patients are coming in more informed, and they can feel comfortable making decisions even more than they could with Google. That's clear in terms of how it's impacting the patients. I think the health systems are still trying to get their arms wrapped around what the appropriate use of AI across the enterprise is." "Now, when it comes to making treatment recommendations, I still think we're in the early stages. There are still many hallucinations. The data sources we're pulling from are still fragmented. Data hygiene and some of that data are not always accurate. So I think there's going to have to be a lot of evolution in how we manage the data and improve interoperability, so that all of the data can start to talk to one another, and we can really have a complete picture before these platforms can really impact care." #DexCare #AIinHealthcare #DigitalHealth #HealthSystems #ClinicalAI #HealthcareInnovation #PatientAccess #DigitalFrontDoor #CareOrchestration #HealthIT #Interoperability #DataQuality #PrecisionMedicine #PersonalizedCare #ClinicianExperience #HealthcareLeadership #DigitalTransformation #HealthTech #HospitalOperations #CallCenterAutomation #EmergencyMedicine dexcare.com Listen to the podcast here
Transcribe →Using Health AI Platforms to Bridge Gaps in Patient Care with Matt Blosl DexCare
2w ago00:16:31Tap to summarizeMatt Blosl, CEO of DexCare, has a core mission to help large health systems use AI responsibly to attract patients and work with them to get appropriate care. While AI's data-processing capabilities are transformative, its use in clinical recommendations remains in its early stages, constrained by fragmented data and the limited availability of validated diagnoses. Matt advises healthcare leaders to adopt a problem-first approach to AI implementation and to use technology to drive significant change rather than just incremental improvements to existing workflows. Matt explains, "Artificial intelligence is interesting. We're still in what I consider to be the Gold Rush phase of a new technology. Certainly one as disruptive as this. So I think a lot of our clients are still trying to figure out what it means. From my perspective, you said it very well. Google or the internet was kind of our first foray into providing patients more access before they even seek care or before they go in to receive care. And what I see right now is that the AI platforms are kind of the next level of that. The richness of the information is greater. And so patients are coming in more informed, and they can feel comfortable making decisions even more than they could with Google. That's clear in terms of how it's impacting the patients. I think the health systems are still trying to get their arms wrapped around what the appropriate use of AI across the enterprise is." "Now, when it comes to making treatment recommendations, I still think we're in the early stages. There are still many hallucinations. The data sources we're pulling from are still fragmented. Data hygiene and some of that data are not always accurate. So I think there's going to have to be a lot of evolution in how we manage the data and improve interoperability, so that all of the data can start to talk to one another, and we can really have a complete picture before these platforms can really impact care." #DexCare #AIinHealthcare #DigitalHealth #HealthSystems #ClinicalAI #HealthcareInnovation #PatientAccess #DigitalFrontDoor #CareOrchestration #HealthIT #Interoperability #DataQuality #PrecisionMedicine #PersonalizedCare #ClinicianExperience #HealthcareLeadership #DigitalTransformation #HealthTech #HospitalOperations #CallCenterAutomation #EmergencyMedicine dexcare.com Download the transcript here
Transcribe →Next Generation Bispecific Antibody Drug Conjugates Improves Targeting of Solid Tumors with Dr. Mayank Gandhi NEOK Bio TRANSCRIPT
2w agoTap to summarizeDr. Mayank Gandhi, CEO of NEOK Bio, discusses the company's work on bispecific antibody drug conjugates and the limitations of conventional ADCs, which target a single antigen. Using a bispecific antibody to target two unique antigens on a tumor can address the shortcomings of earlier approaches by improving delivery of the toxic payload, overcoming tumor heterogeneity, and reducing off-target toxicity. NEOK has drugs in development for prostate cancer, and lung, head, neck, and gastrointestinal tumors. The trend for ADCs is toward multi-specific and multi-payload drugs, though Mayank warns it is not a simple task to go from one to many in designing these drug conjugates. Mayank explains, "There have been a lot of advancements in the last couple of decades, and especially the last few years, in various modalities in the treatment of hematological cancers, as well as to a certain degree in solid tumors. However, for many, many solid tumors, there's still a high unmet need given the still significant outcome, poor outcomes that patients experience, particularly with patients having metastatic disease across a variety of solid tumors. Now, if you look at specific modality like ADC or antibody drug conjugates, which is where NEOK Bio is, there's been a renaissance, if you will, with this modality in the last five to six years, particularly after the approval of a drug called Enhertu, which targets HER2 mutation. Now, many ADCs have been approved with different payloads. And so definitely that's made a dent in a variety of tumors, particularly in hematological cancers and select solid tumors as well." "Conventional ADCs thus far target one antigen or one target on a tumor. So it's an antibody-based approach. The antibody is typically pursuing one specific antigen that's usually an antigen that's expressed on tumors selectively versus normal tissue or normal cells. And then you have a linker and a payload, usually a toxic payload that's conjugated via a linker to the antibody. So that's an antibody drug conjugate construct." "Thus far, all the ADCs approved have been targeting only one antigen with a couple of different payloads. And so our bispecific approach is targeting two different antigens. If we use a bispecific antibody that targets two unique antigens on the tumor, we have more than one place that a potential antibody can bind and deliver the toxic payload. And then we have made some very significant improvements or changes in the antibody itself." #NEOKBio #DrugDevelopment #Innovation #AntibodyDrugConjugates #ADC #Oncology #Biotech#Oncology #SolidTumors #BispecificADC #CancerResearch #TranslationalResearch #MedicalOncology #HematologyOncology #ClinicalTrials #Biotech #Pharma #DrugDevelopment #PrecisionOncology #TumorMicroenvironment #TargetedTherapy NEOKBio.com Listen to the podcast here
Transcribe →Next Generation Bispecific Antibody Drug Conjugates Improves Targeting of Solid Tumors with Dr. Mayank Gandhi NEOK Bio
2w ago00:20:28Tap to summarizeDr. Mayank Gandhi, CEO of NEOK Bio, discusses the company's work on bispecific antibody drug conjugates and the limitations of conventional ADCs, which target a single antigen. Using a bispecific antibody to target two unique antigens on a tumor can address the shortcomings of earlier approaches by improving delivery of the toxic payload, overcoming tumor heterogeneity, and reducing off-target toxicity. NEOK has drugs in development for prostate cancer, and lung, head, neck, and gastrointestinal tumors. The trend for ADCs is toward multi-specific and multi-payload drugs, though Mayank warns it is not a simple task to go from one to many in designing these drug conjugates. Mayank explains, "There have been a lot of advancements in the last couple of decades, and especially the last few years, in various modalities in the treatment of hematological cancers, as well as to a certain degree in solid tumors. However, for many, many solid tumors, there's still a high unmet need given the still significant outcome, poor outcomes that patients experience, particularly with patients having metastatic disease across a variety of solid tumors. Now, if you look at specific modality like ADC or antibody drug conjugates, which is where NEOK Bio is, there's been a renaissance, if you will, with this modality in the last five to six years, particularly after the approval of a drug called Enhertu, which targets HER2 mutation. Now, many ADCs have been approved with different payloads. And so definitely that's made a dent in a variety of tumors, particularly in hematological cancers and select solid tumors as well." "Conventional ADCs thus far target one antigen or one target on a tumor. So it's an antibody-based approach. The antibody is typically pursuing one specific antigen that's usually an antigen that's expressed on tumors selectively versus normal tissue or normal cells. And then you have a linker and a payload, usually a toxic payload that's conjugated via a linker to the antibody. So that's an antibody drug conjugate construct." "Thus far, all the ADCs approved have been targeting only one antigen with a couple of different payloads. And so our bispecific approach is targeting two different antigens. If we use a bispecific antibody that targets two unique antigens on the tumor, we have more than one place that a potential antibody can bind and deliver the toxic payload. And then we have made some very significant improvements or changes in the antibody itself." #NEOKBio #DrugDevelopment #Innovation #AntibodyDrugConjugates #ADC #Oncology #Biotech#Oncology #SolidTumors #BispecificADC #CancerResearch #TranslationalResearch #MedicalOncology #HematologyOncology #ClinicalTrials #Biotech #Pharma #DrugDevelopment #PrecisionOncology #TumorMicroenvironment #TargetedTherapy NEOKBio.com Download the transcript here
Transcribe →How Generative Vision Language AI is Transforming Radiology with Louis Blankemeier Cognita TRANSCRIPT
2w agoTap to summarizeLouis Blankemeier, CEO and Co-Founder of Cognita, describes the significant gap between the number of radiologists and the rising volume and types of medical imaging that need to be reviewed. The Cognita generative visual language model is an advancement over earlier radiology AI applications that were designed to flag single findings. This integrated approach emulates a radiologist by analyzing complex images and generating full draft radiology reports, demonstrating reduced time per case, increased detection of critical findings, and decreased cognitive burden on radiologists. Louis explains, "Radiologists look at a number of different imaging types. So there are X-rays, and these are basically 2D images or 2D projections of the inside of the body. So you see all the organs superimposed on each other in a 2D image. And the radiologists have to take this 2D image and create almost a 3D representation in their head to understand what's going on in the body. They also read CT scans, which use X-ray radiation but take multiple images from different angles of the body. And then you basically reconstruct a 3D video that shows you what the inside of a body looks like. And then there are also MRI scans, which use magnetism to create a video of the inside of the body. And CT and MRI are 3D imaging modalities. So they're both kind of like videos. And you have an ultrasound, which uses sound waves, and you have a long tail of different imaging types. But radiologist spend most of their time looking at X-rays, CT scans, and MRI images." "A vision language model is a model that has eyes, so it can actually look at images, and then the language part describes how we are generating text in the output. And we can actually add one more descriptor to vision language. We can add the term generative. So we're actually generating text in the output of our model. We're generating the radiology report. And this is in contrast to most models out there today that are discriminative. There are these classifier models that are saying, " Is there a disease present or not? And the output is binary. It's zero one. It's not a text report in the output." #Cognita #AIinRadiology #GenerativeAI #VisionLanguageModels #RadiologyWorkflow #DiagnosticImaging #MedicalAI #HealthcareInnovation #RadiologistSupport #ClinicalDecisionSupport #PatientSafety #BurnoutReduction #FDA #BreakthroughDevice #DigitalHealth #HealthTech Cognita.ai Listen to the podcast here
Transcribe →How Generative Vision Language AI is Transforming Radiology with Louis Blankemeier Cognita
2w ago00:18:56Tap to summarizeLouis Blankemeier, CEO and Co-Founder of Cognita, describes the significant gap between the number of radiologists and the rising volume and types of medical imaging that need to be reviewed. The Cognita generative visual language model is an advancement over earlier radiology AI applications that were designed to flag single findings. This integrated approach emulates a radiologist by analyzing complex images and generating full draft radiology reports, demonstrating reduced time per case, increased detection of critical findings, and decreased cognitive burden on radiologists. Louis explains, "Radiologists look at a number of different imaging types. So there are X-rays, and these are basically 2D images or 2D projections of the inside of the body. So you see all the organs superimposed on each other in a 2D image. And the radiologists have to take this 2D image and create almost a 3D representation in their head to understand what's going on in the body. They also read CT scans, which use X-ray radiation but take multiple images from different angles of the body. And then you basically reconstruct a 3D video that shows you what the inside of a body looks like. And then there are also MRI scans, which use magnetism to create a video of the inside of the body. And CT and MRI are 3D imaging modalities. So they're both kind of like videos. And you have an ultrasound, which uses sound waves, and you have a long tail of different imaging types. But radiologist spend most of their time looking at X-rays, CT scans, and MRI images." "A vision language model is a model that has eyes, so it can actually look at images, and then the language part describes how we are generating text in the output. And we can actually add one more descriptor to vision language. We can add the term generative. So we're actually generating text in the output of our model. We're generating the radiology report. And this is in contrast to most models out there today that are discriminative. There are these classifier models that are saying, " Is there a disease present or not? And the output is binary. It's zero one. It's not a text report in the output." #Cognita #AIinRadiology #GenerativeAI #VisionLanguageModels #RadiologyWorkflow #DiagnosticImaging #MedicalAI #HealthcareInnovation #RadiologistSupport #ClinicalDecisionSupport #PatientSafety #BurnoutReduction #FDA #BreakthroughDevice #DigitalHealth #HealthTech Cognita.ai Download the transcript here
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