Lantern Pharma Inc (LTRN) 2023 Q4 法說會逐字稿

Good afternoon and welcome to our fourth-quarter and year-end 2023 earnings call. (Event instructions) A webcast replay of today's conference call will be available on our website at lanternpharma.com shortly after the call. We issue a press release after market close today, summarizing our financial results and progress across the company for the fourth quarter and year ended December 31, 2023. A copy of this release is available through our website at lanternpharma.com, where you will also find a link to the slides management will be referencing on today's call.

下午好，歡迎參加我們的第四季和 2023 年底財報電話會議。（活動說明）今天電話會議的網路廣播重播將在電話會議結束後不久在我們的網站 Lanternpharma.com 上提供。我們今天收盤後發布新聞稿，總結了截至 2023 年 12 月 31 日的第四季度和全年的財務業績和整個公司的進展。新聞稿的副本可透過我們的網站 Lanternpharma.com 取得，您還可以在其中找到指向今天電話會議中將引用的幻燈片管理層的連結。

We would like to remind everyone that remarks about future expectations, performance, estimates, and prospects constitute forward-looking statements for purposes of Safe Harbor provisions under the Private Securities Litigation Reform Act of 1995. Lantern Pharma cautions that these forward-looking statements are subject to risks and uncertainties but may cause actual results to differ materially from those anticipated.

我們想提醒大家，有關未來預期、績效、估計和前景的言論構成前瞻性陳述，符合 1995 年《私人證券訴訟改革法案》中的安全港條款。Lantern Pharma 警告稱，這些前瞻性陳述存在風險和不確定性，但可能導致實際結果與預期有重大差異。

A number of factors could cause actual results to differ materially from those indicated by forward-looking statements, including results of clinical trials and the impact of competition. Additional information concerning factors that could cause actual results to differ materially from those in the forward-looking statements can be found in our annual report on Form 10-K for the year ended December 31, 2023, which is on file with the SEC and available on our website.

許多因素可能導致實際結果與前瞻性陳述所示的結果有重大差異，包括臨床試驗結果和競爭的影響。有關可能導致實際結果與前瞻性陳述中的結果存在重大差異的因素的更多信息，請參閱我們截至 2023 年 12 月 31 日的 10-K 表格年度報告，該報告已向 SEC 備案並可供查閱在我們的網站上。

Forward-looking statements made on this conference call are as of today, March 18, 2024, and Lantern Pharma does not intend to update any of these forward-looking statements to reflect events or circumstances that occur after today, unless required by law. The webcast replay of the conference call and webinar will be available on Lantern's website.

本次電話會議中所做的前瞻性陳述截至今天，即 2024 年 3 月 18 日，除非法律要求，否則 Lantern Pharma 不打算更新任何這些前瞻性陳述以反映今天之後發生的事件或情況。電話會議和網路研討會的網路直播重播將在 Lantern 網站上提供。

On today's webcast, we have Lantern Pharma CEO, Panna Sharma; and CFO, David Margrave. Panna will start things off with an overview of Lantern strategy and business model and highlight recent achievements in our operations, after which, David will discuss our financial results. This will be followed by some concluding comments from Panna, and then we'll open the call for Q&A.

在今天的網路廣播中，我們有 Lantern Pharma 執行長 Panna Sharma；財務長大衛·馬格雷夫。Panna 將首先概述 Lantern 策略和商業模式，並重點介紹我們最近在營運中的成就，之後 David 將討論我們的財務表現。接下來是 Panna 的一些總結性評論，然後我們將開始問答環節。

I'd now like to turn the call over to Panna Sharma, President and CEO of Lantern Pharma. Panna, please go ahead.

我現在想將電話轉給 Lantern Pharma 總裁兼執行長 Panna Sharma。潘娜，請繼續。

Hello, everyone, and thank you for joining us this afternoon to hear about our fourth-quarter and fiscal-year 2023 results and corporate progress. As many of you have heard me say in the past, computational and AI-driven approaches are increasing their presence and usage at both large and emerging pharma companies for all facets of drug discovery and development. Lantern's leadership in the innovative use of AI and machine learning to transform cost and timelines in the development of precision oncology therapies should yield significant returns for investors and patients as our industry matures and adopts an AI-centric and data-first approach to drug development.

大家好，感謝您今天下午加入我們，聆聽我們第四季和 2023 財年的業績以及公司進展。正如你們許多人過去聽我說過的那樣，計算和人工智慧驅動的方法正在增加大型和新興製藥公司在藥物發現和開發的各個方面的存在和使用。隨著我們的行業日趨成熟並採用以人工智慧為中心和數據優先的藥物開發方法，Lantern 在創新利用人工智慧和機器學習來改變精準腫瘤治療開發的成本和時間表方面的領導地位將為投資者和患者帶來可觀的回報。

2023 was a transformational year for Lantern Pharma across many measures. We launched multiple clinical trials for our -- using our AI-guided drug candidates. We have multiple peer-reviewed publications and posters for our drug candidates and for our RADR AI platform. Our AI platform advanced, reaching over 60 billion data points last year, and now is on the road to reaching over 100 billion this year. With significant and efficient expansion of our clinical infrastructure and operations team, this allows us to efficiently move our trials forward and maintain control over the data and operations of our clinical assets.

從許多方面來看，2023 年對 Lantern Pharma 來說都是轉型的一年。我們使用人工智慧引導的候選藥物啟動了多項臨床試驗。我們的候選藥物和 RADR AI 平台擁有多份經過同行評審的出版物和海報。我們的人工智慧平台取得了進步，去年達到了超過 600 億個數據點，今年預計將達到超過 1000 億個。隨著我們的臨床基礎設施和營運團隊的顯著而高效的擴展，這使我們能夠有效地推進試驗並保持對臨床資產的數據和營運的控制。

We are also advancing a very exciting new company, Starlight Therapeutics, which is entirely focused on CNS cancers and an area where there has been no single-approved therapy as monotherapy in nearly 18 years. We filed 11 patent applications last year across our drug candidates and our AI platform, and we've continued to show very strong, focused fiscal discipline.

我們也正在推動一家非常令人興奮的新公司 Starlight Therapeutics，該公司完全專注於中樞神經系統癌症以及近 18 年來沒有單一療法作為單一療法的領域。去年，我們針對候選藥物和人工智慧平台提交了 11 項專利申請，我們繼續表現出非常強大、專注的財務紀律。

Our team has accomplished a lot and is about 24 people today, small, but focused and comprised of leaders at every level high-value contributors. They've made significant strides over the past quarter and throughout 2023 across all our programs and also with our AI platform, RADR. RADR, which has guided the rapid and efficient development of three AI-guided drugs into clinical trials at a pace and cost that has traditionally been unheard of in our industry.

我們的團隊取得了許多成就，目前約有 24 人，規模雖小，但專注，由各個層級的領導者和高價值貢獻者組成。在過去一個季度和整個 2023 年，他們在我們的所有專案以及我們的 AI 平台 RADR 上都取得了重大進展。RADR 指導了三種人工智慧引導藥物的快速高效開發進入臨床試驗，其速度和成本在我們行業中是聞所未聞的。

Our team has been focused on executing our mission of transforming the oncology drug discovery and development process, especially as we bring our clinical-stage drug candidates into human clinical trials, two that are now in Phase 1 as part of our synthetic lethality franchise and one that is in Phase 2. All of our clinical trials now have enrolled and dosed patients, and we expect to have data to share with you later this year as enrollment progresses.

我們的團隊一直專注於執行我們改變腫瘤藥物發現和開發流程的使命，特別是當我們將臨床階段候選藥物納入人體臨床試驗時，其中兩個目前處於第一階段，作為我們合成致死特許經營權的一部分，還有一個那是在第二階段。我們所有的臨床試驗現已入組並給患者服用藥物，隨著入組進展，我們預計將在今年稍後與您分享數據。

Our team and many clinicians are particularly excited about and interested in the programs for our first-in-human drug candidates, LP-184 and LP-284. Also, our unique drug, LP-300, which we in-licensed and rescued, is aimed at never smokers who have been impacted by non-small-cell lung cancer but have failed other treatment options.

我們的團隊和許多臨床醫生對我們的首個人體候選藥物 LP-184 和 LP-284 計畫感到特別興奮和感興趣。此外，我們獲得許可並拯救的獨特藥物 LP-300，針對的是受非小細胞肺癌影響但其他治療方案失敗的從不吸煙者。

Lung cancer among never smokers is a growing problem, not only in the US but globally. And we've been successful in moving towards regulatory allowance for commencing our trial in Japan, Taiwan, and South Korea, where the incidence of non-small cell lung cancer among never smokers is nearly 2.5 to 3 times that here in the US.

從不吸菸者的肺癌是一個日益嚴重的問題，不僅在美國，而且在全球。我們已經成功地獲得了在日本、台灣和韓國開展試驗的監管許可，這些國家從不吸煙者的非小細胞肺癌發病率幾乎是美國的 2.5 至 3 倍。

We also continue to make significant progress on the launch of our clinical stage CNS and brain cancer focused subsidiary, Starlight Therapeutics. This is a company that has been largely developed as a result of data, AI methods, computational approaches to optimize and maximize our insights about a molecule. About a year ago, we announced the formation of the subsidiary. We recruited a CMO last quarter in the fourth quarter, and now we're preparing to go into Phase 1b/2 clinical trials.

我們也在推出專注於中樞神經系統和腦癌臨床階段的子公司 Starlight Therapeutics 方面繼續取得重大進展。這家公司的發展很大程度上得益於數據、人工智慧方法和計算方法，以優化和最大化我們對分子的洞察力。大約一年前，我們宣布成立子公司。上個季度我們在第四季招募了一位CMO，現在我們正準備進入1b/2期臨床試驗。

We've also made major progress in developing the next major leg of our discovery efforts, which we focused on drug conjugates, including antibody drug conjugates. Specifically, we've now engineered a cryptophycin-linked antibody drug conjugate, which we're developing in a highly efficient manner with our collaborative partners, academic partners in Germany. I'll talk a little bit -- more about that later in this call.

我們在開發我們發現工作的下一個主要階段方面也取得了重大進展，我們的重點是藥物綴合物，包括抗體藥物綴合物。具體來說，我們現在設計了一種隱藻素連接的抗體藥物綴合物，我們正在與我們的合作夥伴、德國的學術夥伴以高效的方式開發這種藥物。我將在本次電話會議的稍後部分詳細討論這一點。

Our progress across our preclinical assets and our clinical programs has been very focused, very efficient, and was in large part guided by our AI platform's latest functionality, capability, and modules, modules like our antibody drug conjugate module. We released some exciting data earlier this quarter, which we concluded as part of our collaboration with University Bielefeld (sic - Bielefeld University). But in particular, in that collaboration, we found that we had excellent control over the cystine-engineered proteins, and that allowed us to have great control of the bio conjugation process. And we also saw very high potency in the picomolar range across six solid tumors, many of them with huge clinical need, in particular in medium expressing HER2 cancers, which is a real unmet need in cancer care.

我們的臨床前資產和臨床項目的進展非常專注、非常高效，並且在很大程度上是由我們的人工智慧平台的最新功能、能力和模組（如我們的抗體藥物偶聯物模組）引導的。我們在本季早些時候發布了一些令人興奮的數據，這些數據是我們與比勒費爾德大學合作的一部分（原文如此-比勒費爾德大學）。但特別是，在那次合作中，我們發現我們對胱胺酸工程蛋白具有出色的控制，這使我們能夠很好地控制生物綴合過程。我們也看到皮摩爾範圍內的六種實體腫瘤具有非常高的效力，其中許多具有巨大的臨床需求，特別是在中等表達的 HER2 癌症中，這是癌症治療中真正未滿足的需求。

Additionally, we continue to enhance and develop our AI platform for cancer drug development. RADR, our platform, we think is revolutionizing the way we model, predict, and understand drug cancer interactions, enabling us to advance our nearly developed drug programs from initial insights to first-in-human clinical trials in an average of less than two years and at a cost of under $2 million per program. It's a milestone unheard of in the realm of oncology drug discovery.

此外，我們繼續增強和開發用於癌症藥物開發的人工智慧平台。我們認為 RADR 平台正在徹底改變我們建模、預測和理解藥物癌症相互作用的方式，使我們能夠在平均不到兩年的時間內將我們即將開發的藥物項目從最初的見解推進到首次人體臨床試驗每個項目的成本不到200 萬美元。這是腫瘤藥物發現領域中聞所未聞的里程碑。

Our leadership in the innovative use of AI machine learning to transform cost and timelines has allowed us to bring three molecules to market with teams, cost, and efficiency that is only beginning to make a massive impact. We think year over year, we'll continue to make improvements and keen in to refine and make our process more efficient, more precise, and potentially even more powerful.

我們在創新利用人工智慧機器學習來改變成本和時間安排方面處於領先地位，這使我們能夠將三種分子推向市場，其團隊、成本和效率才剛開始產生巨大影響。我們認為，年復一年，我們將繼續做出改進，並熱衷於完善，使我們的流程更有效率、更精確，甚至可能更強大。

During 2023, we achieved our goal of reaching 60 billion data points, growing that cancer-focused data more in one year than we had in the prior three years. We expect these massive leaps -- these increase in the pace to continue, and our team expects to reach over 100 billion this year, and this data growth and data ingestion will be automated. It will free up our teams to focus more on intelligent curation and analysis and also on creating upstream engineer datasets from the raw data to solve more specific problems that can make use of generative AI and generative models. This golden age of AI in medicine is just beginning, and it's being powered by large-scale, highly available computing power, massive data storage.

2023 年，我們實現了達到 600 億個數據點的目標，一年內以癌症為中心的數據增長量超過了前三年。我們預計這些巨大的飛躍 - 這些步伐的加快將繼續下去，我們的團隊預計今年將達到 1000 億以上，並且這種數據增長和數據攝取將實現自動化。它將讓我們的團隊更加專注於智慧管理和分析，並從原始數據創建上游工程師資料集，以解決可以利用生成人工智慧和生成模型的更具體的問題。醫學人工智慧的黃金時代才剛開始，它的驅動力是大規模、高可用的運算能力和大量資料儲存。

And additionally, it is being bought -- fed by healthcare, patient, cancer data. All of these data, which is more widely available at an increasing levels of quality higher than ever before. We believe the companies that harnesses capabilities in biotech and more appropriately really the tech bio industry will become long-term leaders that create massive value for patients, for investors, and for our industry.

此外，它是由醫療保健、患者、癌症數據提供的。所有這些數據都以比以往任何時候都更高的品質水準得到更廣泛的使用。我們相信，利用生物技術（更準確地說是科技生物產業）能力的公司將成為長期領導者，為患者、投資者和我們的產業創造巨大價值。

Lantern Pharma is among the leaders in this transformation of the pace risk and cost of oncology drug discovery and development. This transformation has the promise to not only make medicines faster, cheaper, and with increased precision for patients, but also to help change the direction of R&D productivity and output in the pharma industry.

Lantern Pharma 是腫瘤藥物發現和開發的速度風險和成本轉變的領導者之一。這種轉變不僅有望使藥品更快、更便宜、為患者提供更高的精確度，而且有助於改變製藥業研發生產力和產出的方向。

In the past three years, we have successfully developed and launched 11 additional programs, a testament to the agility, efficiency, and groundbreaking nature of our approach. On average, these programs are advancing from initial AI insights to first-in-human clinical trials in just 2.5 years and an average cost of $2 million per program, metrics unheard of in oncology drug discovery.

在過去三年中，我們成功開發並啟動了 11 個其他項目，證明了我們方法的敏捷性、效率和突破性。平均而言，這些項目從最初的人工智慧見解發展到首次人體臨床試驗只花了短短 2.5 年的時間，每個項目的平均成本為 200 萬美元，這是腫瘤藥物發現中聞所未聞的指標。

In fact, in a recent study published by Drug Discovery Today, it was reported that nearly half of the 16 largest pharma companies had negative R&D productivity over the last 18 to 20 years, with Big Pharma collectively spending close to $3 billion per drug approval. These are startling figures, and they serve as a stark reminder that the traditional model of Big Pharma R&D is not a sustainable or effective strategy, and it is not the right approach to improve drug pricing for drug availability. With escalating economic and political pressures over drug prices, it's clear that our industry needs to rethink its approach fundamentally, and we believe Big Pharma will increase adoption of AI and computational approaches, data-first approaches to elevate above this major hurdle sitting in front of us.

事實上，《今日藥物發現》最近發表的一項研究顯示，在過去18 到20 年裡，16 家最大的製藥公司中近一半的研發生產力為負，大型製藥公司在每個藥物批准上總共花費了近30 億美元。這些數字令人震驚，它們清楚地提醒人們，大型製藥公司的傳統研發模式不是可持續或有效的策略，也不是提高藥品定價以提高藥品供應量的正確方法。隨著藥品價格帶來的經濟和政治壓力不斷升級，很明顯，我們的行業需要從根本上重新思考其方法，我們相信大型製藥公司將增加對人工智能和計算方法、數據優先方法的採用，以克服擺在我們面前的這主要障礙。

Now, these specific instances of value creation along with the development of an entirely new company, which will be a clinical-stage Starlight, whose sole focus will be on these intractable CNS and brain cancers, demonstrates that Lantern continues to be at the forefront of a transformative approach to oncology drug discovery. We're reaching speeds and efficiency that we believe are setting new standards in developing cancer medicines.

現在，這些價值創造的具體實例以及一家全新公司的發展，這家公司將成為臨床階段的Starlight，其唯一的重點將是這些棘手的中樞神經系統和腦癌，這表明Lantern 繼續處於癌症治療領域的前沿。我們正在達到的速度和效率，我們相信這正在為開發癌症藥物設定新標準。

As we continue to accelerate the pace at which we're developing and validating insights that can lead to meaningful drug assets that we can partner, license, sell in the future, we believe that we're very well-positioned to partner these drug assets out to larger companies.

隨著我們繼續加快開發和驗證見解的步伐，這些見解可以帶來有意義的藥物資產，我們可以在未來合作、許可、銷售這些資產，我們相信我們處於非常有利的地位來與這些藥物資產合作到更大的公司。

At the same time, our CFO, David Margrave, will cover shortly, we have a very strong cash position, approximately $41.3 million in cash, cash equivalents, and marketable securities, and we're carefully utilizing that to make meaningful progress in a disciplined manner. We're going after indications that are needed, we're going after studies that help validate insights, and we're collecting data that will power our portfolio.

同時，我們的財務長David Margrave 很快就會介紹，我們擁有非常強大的現金頭寸，大約有4,130 萬美元的現金、現金等價物和有價證券，我們正在謹慎地利用這些資金，在嚴格的紀律約束下取得有意義的進展。我們正在尋找所需的跡象，我們正在進行有助於驗證見解的研究，並且我們正在收集將為我們的投資組合提供支援的數據。

We believe our approach is the future of developing cancer therapies, where data can be used to rapidly accelerate programs, de-risk the identification of cancer subtypes, most likely to be responsive; use biomarker profiling to figure patient profiles and needs out earlier in the process; and progress these potentially life-changing medicines and with economics that have not been seen in our industry.

我們相信我們的方法是開發癌症療法的未來，其中數據可用於快速加速計劃，降低癌症亞型識別的風險，最有可能做出反應；使用生物標記分析來了解患者概況並在此過程的早期階段確定需求；並以我們行業中前所未見的經濟效益來開發這些可能改變生活的藥物。

Now, let's turn to some specific highlights of our financial results during the fourth quarter and for the year and 2023. I'll now turn the call over to our CFO, David Margrave, who will provide an overview of our second quarter financial results -- of our fourth-quarter financial results. David?

現在，讓我們來看看第四季度、全年和 2023 年財務業績的一些具體亮點。我現在將把電話轉給我們的財務長 David Margrave，他將概述我們第二季的財務表現以及第四季的財務表現。大衛？

Thank you, Panna, and good afternoon, everyone. I'll now share some financial highlights from our fourth quarter and full year ended December 31, 2023. I'll start with a review of the fourth quarter.

謝謝潘納，大家下午好。現在，我將分享截至 2023 年 12 月 31 日的第四季和全年的一些財務亮點。我將從第四季的回顧開始。

Our general and administrative expenses were approximately $1.3 million for the fourth quarter of 2023, down somewhat from approximately $1.6 million in the prior-year period. R&D expenses were approximately $3.6 million for the fourth quarter of 2023, up from approximately $2.3 million in the fourth quarter of 2022. We recorded a net loss of approximately $4.2 million for the fourth quarter of 2023, or $0.39 per share, compared to a net loss of approximately $ 3.4 million, or $0.31 per share, for the fourth quarter of 2022.

2023 年第四季我們的一般和管理費用約為 130 萬美元，略低於去年同期的約 160 萬美元。2023 年第四季的研發費用約為 360 萬美元，高於 2022 年第四季的約 230 萬美元。我們的 2023 年第四季淨虧損約為 420 萬美元，即每股 0.39 美元，而 2022 年第四季的淨虧損約為 340 萬美元，即每股 0.31 美元。

For the full year 2023, our R&D expenses were approximately $11.9 million, up from approximately $8.6 million for 2022. This increase was primarily attributable to increases in research studies of approximately $2.98 million, increases in research and development payroll expenses of approximately $1.2 million, and increases in consulting expenses of approximately $160,000. These increases were partially offset by decreases in product candidate manufacturing-related expenses of approximately $631,000 and decreases of approximately $459,000 in payments to Allarity Therapeutics.

2023 年全年，我們的研發費用約為 1,190 萬美元，高於 2022 年的約 860 萬美元。這一增長主要歸因於研究費用增加約 298 萬美元、研發工資費用增加約 120 萬美元以及諮詢費用增加約 16 萬美元。這些增長被候選產品製造相關費用減少約 631,000 美元以及支付給 Allarity Therapeutics 的費用減少約 459,000 美元所部分抵消。

During the year ended December 31, 2022, we released an escrow payment of approximately $459,000 to Allarity Therapeutics, and there was not a release of escrow payment amounts to Allarity during the year ended December 31, 2023. Manufacturing-related expenses for the year ended December 31, 2022, were also reduced by $935,000 as a result of a payment we received in July 2022 from one of our service providers in connection with the resolution of a difference of views regarding the service provider agreement.

截至2022年12月31日止年度，我們向 Allarity Therapeutics 發放了約 459,000 美元的託管付款，且截至 2023 年 12 月 31 日止年度，未向 Allarity 發放託管付款金額。截至 2022 年 12 月 31 日止年度的製造相關費用也減少了 935,000 美元，原因是我們於 2022 年 7 月從我們的一家服務提供者收到了與解決服務提供者協議意見分歧有關的付款。

Our general and administrative expenses for 2023 were approximately $6.0 million, up slightly from $5.9 million for 2022. The increase was primarily attributable to increases in payroll and compensation expense and other professional fees. Our R&D expenses continued to exceed our G&A expenses by a strong margin, reflecting our focus on advancing our product candidates and pipeline.

我們 2023 年的一般和管理費用約為 600 萬美元，略高於 2022 年的 590 萬美元。增加的主要原因是工資和薪酬費用以及其他專業費用的增加。我們的研發費用持續大幅超過一般管理費用，反映出我們專注於推進我們的產品候選人和管道。

For the full year 2023, net loss was approximately $15.96 million, or $1.47 per share, compared to $14.3 million, or $1.31 per share, for 2022. Our loss from operations for the 2023 calendar year was partially offset by interest income and other income net totaling approximately $1.9 million. Our cash position, which includes cash equivalents and marketable securities, was approximately $41.3 million as of December 31, 2023. We anticipate this balance will provide us with a cash runway into at least Q3 of 2025. Importantly, we believe our solid financial position will fuel continued growth and evolution of our RADR AI platform, accelerate the development of our portfolio of targeted oncology drug candidates, and allow us to introduce additional targeted programs and collaboration opportunities in a capital-efficient manner.

2023 年全年淨虧損約 1,596 萬美元，每股 1.47 美元，而 2022 年淨虧損為 1,430 萬美元，即每股 1.31 美元。我們 2023 年曆年的營運損失被總計約 190 萬美元的利息收入和其他收入淨額部分抵銷。截至 2023 年 12 月 31 日，我們的現金部位（包括現金等價物和有價證券）約為 4,130 萬美元。我們預計這一餘額將為我們提供至少到 2025 年第三季的現金跑道。重要的是，我們相信我們穩健的財務狀況將推動我們的RADR AI 平台的持續成長和發展，加速我們的標靶腫瘤候選藥物組合的開發，並使我們能夠以資本高效的方式引入更多的有針對性的專案和合作機會。

As of December 31, 2023, we had 10,721,192 shares of common stock outstanding, outstanding warrants to purchase 177,998 shares, and outstanding options to purchase 1,091,196 shares. These warrants and options, combined with our outstanding shares of common stock, give us a total fully diluted shares outstanding of approximately 11.99 million shares as of year-end 2023. In November of '23, we were able to reduce our outstanding share count through the purchase of 145,348 shares of Lantern common stock at a purchase price of $3.44 per share.

截至 2023 年 12 月 31 日，我們擁有 10,721,192 股已發行普通股、已發行認股權證以購買 177,998 股，以及已發行選擇權以購買 1,091,196 股。這些認股權證和選擇權，加上我們已發行的普通股，截至 2023 年底，我們的完全稀釋後已發行股票總數約為 1,199 萬股。2023 年 11 月，我們以每股 3.44 美元的價格購買了 145,348 股 Lantern 普通股，從而減少了流通股數量。

Our team continues to be very productive under a hybrid operating model. We currently have 21 employees and 3 FTE consultants, focused primarily on leading and advancing our research and drug development efforts. We see this number expanding slightly in coming quarters as we add additional experienced and talented individuals to help advance our mission.

我們的團隊在混合營運模式下持續保持高效率。我們目前擁有 21 名員工和 3 名 FTE 顧問，主要致力於領導和推進我們的研究和藥物開發工作。隨著我們增加更多經驗豐富、才華橫溢的人員來幫助推進我們的使命，我們預計這一數字在未來幾季將略有擴大。

I'll now turn the call back over to Panna for an update on some of our development programs. Panna?

現在我將把電話轉回潘納，以了解我們一些開發計劃的最新情況。潘納？

Thank you, David. As we mentioned earlier in the call, one of the areas that we're very excited about is Starlight Therapeutics. We hired Dr. Marc Chamberlain during the fourth quarter and has made excellent progress on advancing our clinical trial design in both adult and pediatric CNS cancers, and we expect to launch the initial adult trial during the second half of this year. This is incumbent on getting the type of safety and early efficacy signal from our current ongoing LP-184 trial, which is in Phase 1, and at this point over halfway enrolled. So we will share more on the progress of this clinical trial in the coming weeks.

謝謝你，大衛。正如我們之前在電話會議中提到的，我們非常興奮的領域之一是星光療法。我們在第四季度聘請了 Marc Chamberlain 博士，並在推進成人和兒童中樞神經系統癌症的臨床試驗設計方面取得了巨大進展，我們預計將在今年下半年啟動初步的成人試驗。我們有責任從我們目前正在進行的 LP-184 試驗中獲得安全性和早期療效信號，該試驗處於第一階段，目前已入組一半以上。因此，我們將在未來幾週內分享更多有關該臨床試驗進展的資訊。

Now, Starlight's focus on CNS cancers came from initial screens to look at cancers that exhibited exquisite preclinical and in silico-based evidence of sensitivity to LP-184. It was essentially born from billions of data points, and we had not yet gone to in vitro and in vivo observations. We naturally moved quickly to in vitro and in vivo observations as it was clear that the data was suggesting that GBM, and actually several other brain cancers, should be very sensitive given the genomic profile, given the interactive design, and given the levels of DNA damage repair or PTGR1 we saw in those brain cancers.

現在，Starlight 對 CNS 癌症的關注來自於對癌症的初步篩選，這些癌症表現出對 LP-184 敏感的精緻臨床前和基於電腦的證據。它本質上是由數十億個數據點產生的，我們還沒有進行體外和體內觀察。我們自然而然地迅速轉向體外和體內觀察，因為很明顯，數據表明，考慮到基因組圖譜、交互設計和 DNA 水平，GBM 以及實際上其他幾種腦癌應該非常敏感。修復或PTGR1。

Now, let me share some background about the Starlight, which is 100% owned by Lantern, putting, of course, our shareholders, and we believe will have the potential to be another very positive impact on our investors as we monetize this unique asset, the patents, and of course, the insights. Starlight Therapeutics is targeted in several cancers, both adult and pediatric. The five-year survival rate in many of these cancers is super low despite advances in cancer therapies. We think globally there are over 500,000 patients that we can target. We have an orphan designation already for GBM and ATRT. We also have the rare pediatric disease designation. We have world-class collaborators with Hopkins, UT Health San Antonio, and the Children's Brain Tumor Network, which is one of our newer collaborators.

現在，讓我分享一些關於Starlight 的背景，它由Lantern 100% 擁有，當然還有我們的股東，我們相信，當我們將這一獨特資產貨幣化時，它有可能對我們的投資者產生另一個非常正面的影響，專利，當然還有見解。Starlight Therapeutics 的目標是治療多種癌症，包括成人和兒童。儘管癌症治療取得了進步，但許多癌症的五年存活率仍然很低。我們認為全球範圍內我們可以針對超過 50 萬名患者。我們已經為 GBM 和 ATRT 指定了孤兒藥。我們還有罕見的兒科疾病名稱。我們與霍普金斯大學、德州大學聖安東尼奧分校健康中心以及兒童腦腫瘤網絡（我們的新合作者之一）擁有世界級的合作者。

Additionally, there are over 120 types of central nervous system and brain cancers. So it's a wide open area, although 50% of them do tend to be GBM and other high-grade gliomas, and we will be enrolling some of those patients in the early Phase 1a study to determine maximum tolerated dose. There are many other brain cancers, both primary and secondary, that Starlight has an option of going after. And we think this can be a pivotal drug, STAR-001, in the future of brain cancer therapies.

此外，還有 120 多種中樞神經系統癌和腦癌。因此，這是一個廣闊的開放領域，儘管其中 50% 確實往往是 GBM 和其他高級神經膠質瘤，我們將在早期 1a 期研究中招募其中一些患者以確定最大耐受劑量。星光還可以選擇治療許多其他原發性和繼發性腦癌。我們認為 STAR-001 可能成為未來腦癌治療的關鍵藥物。

Now, let's talk a little bit about the trials that are planned for STAR-001. As I mentioned, the Phase 1a will be done by Lantern. The dosage and safety data obtained in the Phase 1 trial, which is now about halfway through, will be used to advance the indications for a future Phase 1b/2 trial to be sponsored jointly by Lantern and our wholly owned subsidiary, Starlight Therapeutics. The markets we think globally are in excess of $5 billion. and this brings the total market for LP-184's indications, both in CNS and in other solid tumors, to being in the range of about $10 billion to $12 billion-plus.

現在，我們來談談 STAR-001 計劃進行的試驗。正如我所提到的，1a 階段將由 Lantern 完成。目前大約已過半的 1 期試驗中獲得的劑量和安全性數據將用於推進未來 1b/2 期試驗的適應症，該試驗將由 Lantern 和我們的全資子公司 Starlight Therapeutics 聯合贊助。我們認為全球市場規模超過 50 億美元。這使得 LP-184 的適應症（無論是中樞神經系統還是其他實體腫瘤）的總市場達到約 100 億至 120 億美元以上。

So you can see why we're particularly excited about this molecule, why we spent a lot of time understanding its molecular profile, understanding the triggers of patient response, understanding the indications where it will be most sensitive, and then also developing patents around combining this unique drug with other therapies. So this is one of the most well-characterized molecules prior to even getting into Phase 1, let alone now once we received the Phase 1 data. We are very excited about this molecule. We'll have data this year on the Phase 1 trial. And more importantly, we'll have data that allow us to go into combination trials and into CNS with Starlight Therapeutics.

所以你可以明白為什麼我們對這個分子特別興奮，為什麼我們花了很多時間來了解它的分子概況，了解患者反應的觸發因素，了解它最敏感的適應症，然後還圍繞組合開發專利這種獨特的藥物與其他療法結合。因此，這是在進入第一階段之前最充分錶徵的分子之一，更不用說現在我們收到第一階段資料後了。我們對這個分子感到非常興奮。今年我們將獲得第一階段試驗的數據。更重要的是，我們將獲得數據，使我們能夠進行組合試驗並與 Starlight Therapeutics 一起進入 CNS 領域。

Let's go to another area that our team has been working on, and this is a highly promising area of antibody drug conjugates. This is a very expensive area, which we believe going to crush the costs not only in early-stage development perhaps, but also in later-stage development. It's a high-growth area for oncology.

讓我們轉到我們團隊一直在研究的另一個領域，這是一個非常有前途的抗體藥物偶聯物領域。這是一個非常昂貴的領域，我們相信這不僅會降低早期開發的成本，而且還會降低後期開發的成本。這是腫瘤學的高成長領域。

Earlier this year, we announced our advancements of the ADC program that we're working on in combination with the University of Bielefeld in Germany. Much of this work was accomplished in late '23, and Dr. Sewald's lab as part of the magic bullet consortium.

今年早些時候，我們宣布了與德國比勒費爾德大學合作開發的 ADC 計畫的進展。這項工作的大部分工作是在 23 世紀末完成的，Sewald 博士的實驗室是 magicBullet 聯盟的一部分。

We were able to take our cryptophycin antibody drug conjugate and advance it not only in proven synthesis and via conjugation, but develop a preclinical proof of concept that it worked really well in an area of high unmet need, which is moderate HER2 expression. Our kill rates with this cryptophycin drug payload averaged 80% across a number of cancer cell lines. And more importantly, we saw that it was about 10 times more potent than some of the existing ADCs that used a very common payload, MMAE. This is a very, very efficient antitumor activity, and it was, more importantly, give us EC-50 values. That means we're about 50% of cells are the cancers -- cancer cells of interest are killed in the picomolar to actually single-digit nanomolar range, even more challenging cancers.

我們能夠採用我們的隱藻素抗體藥物綴合物，不僅在經過驗證的合成和綴合方面對其進行改進，而且還開發了臨床前概念證明，證明它在高度未滿足需求的領域（即中等HER2 表達）確實發揮了良好的作用。我們使用這種隱藻素藥物有效負載對多種癌細胞系的殺傷率平均為 80%。更重要的是，我們發現它比一些使用非常常見的有效負載 MMAE 的現有 ADC 的效力大約高 10 倍。這是一種非常非常有效的抗腫瘤活性，更重要的是，它為我們提供了 EC-50 值。這意味著大約 50% 的細胞是癌症——感興趣的癌細胞在皮摩爾至個位數納摩爾範圍內被殺死，甚至是更具挑戰性的癌症。

We're now doing additional studies to develop and further validate these findings and most importantly, do what we really think is most critical in these studies to obtain a deeper understanding of the genomic and biomarker correlates of payload efficacy. This is really one of the most important things is to understand what is driving that kind of response. How can we repeat it? How can we pinpoint it? And what other things do we need to be aware of as we go after these cancers?

我們現在正在做更多的研究來開發和進一步驗證這些發現，最重要的是，做我們真正認為在這些研究中最關鍵的事情，以獲得對有效負載功效的基因組和生物標記相關性的更深入的了解。這確實是最重要的事情之一，就是了解是什麼推動了這種反應。我們怎樣才能重複呢？我們要怎麼查明它呢？在治療這些癌症時，我們還需要注意哪些事情？

So again, we're taking a data-first approach. We think this is going to save us a lot of time, energy, and money. It can be an asset that we believe can be very licensable, partnerable, or even spin out after we do Starlight. So again, we've got a lot of great assets that are following up to our existing clinical trial assets that are now in Phase 2 and Phase 1.

因此，我們再次採取數據優先的方法。我們認為這將為我們節省大量時間、精力和金錢。我們認為它可以是一項非常可授權、可合作的資產，甚至可以在我們完成星光計畫後分拆出來。再說一遍，我們擁有許多優秀的資產，這些資產正在跟進我們目前處於第二階段和第一階段的現有臨床試驗資產。

I also want to take some time in this call to update you on some critical informational updates. A major part of our business is to inform, educate, and share with the general public and with the oncology community and with our stakeholders details about our programs and efforts. It's an area that we want to be better at. It's an area we want to focus on. And we just launched an effort that we're calling Webinar Wednesday.

我還想在這次電話會議中花一些時間向您通報一些重要的最新資訊。我們業務的一個主要部分是向公眾、腫瘤學界以及利益相關者通報、教育和分享我們的計劃和努力的詳細資訊。這是我們希望做得更好的領域。這是我們想要關注的領域。我們剛剛發起了一項名為「週三網路研討會」的活動。

So our first webinar series will be rolled out. We're going to have a webinar as part of this effort with Dr. Joseph Treat of Fox Chase Cancer Center. This will be a LP-300. Dr. Treat's a leading expert in lung malignancies, and he will be hosting our first webinar series in the coming month.

因此，我們的第一個網路研討會系列將推出。作為這項工作的一部分，我們將與福克斯蔡斯癌症中心的 Joseph Treat 博士一起舉辦網路研討會。這將是 LP-300。Treat 博士是肺部惡性腫瘤的領先專家，他將在下個月主持我們的首個網路研討會系列。

This will be followed by a webinar on Starlight from our very own Dr. Marc Chamberlain. He's a tremendous resource; a virtually human encyclopedia; and store of knowledge about CNS and brain cancers, CNS trials, history of drugs in CNS and brain cancers, history of drug regiments, failed and successful across both pediatric and adult CNS cancers. I'm very fortunate to have him, and he'll be hosting their second webinar focused on Starlight.

隨後，我們的馬克張伯倫 (Marc Chamberlain) 博士將舉辦一場關於星光的網路研討會。他是一個巨大的資源；幾乎是人類百科全書；以及有關中樞神經系統和腦癌、中樞神經系統試驗、中樞神經系統和腦癌藥物歷史、藥物治療歷史、兒童和成人中樞神經系統癌症失敗和成功的知識庫。我很幸運能有他，他將主持他們的第二次網路研討會，專注於星光。

And that will be followed by another webinar about our LP-184 clinical trial, which again is about halfway enrolled, and that will be with Dr. Igor Astsaturov of Fox Chase and will focus heavily on pancreatic and other cancers, challenging tumors that seem to be very responsive to our drug candidate. In fact, it seems that the more aggressive these cancers are recurrent, they have higher levels of PTGR1. And that same markers actually drives the activity of the molecule. So inversely, the more aggressive and recurrent, the better our drug seems to work so far, and we're going to now obviously trying to design future trials using the data from the Phase 1 and the data we have from our in silico and preclinical work.

隨後將舉行另一場關於我們的LP-184 臨床試驗的網路研討會，該試驗的招募工作已過半，將由Fox Chase 的Igor Astsaturov 博士主持，重點關注胰腺癌和其他癌症，挑戰那些似乎難以控制的腫瘤。事實上，似乎這些癌症復發的侵襲性越大，它們的 PTGR1 水平就越高。這些相同的標記實際上驅動了分子的活性。因此，相反，越具有攻擊性和復發性，我們的藥物到目前為止似乎效果越好，我們現在顯然將嘗試使用第一階段的數據以及我們從電腦和臨床前獲得的數據來設計未來的試驗工作。

As I mentioned earlier in our call, this past quarter, our poster for AACR 2024 was selected. It focuses on the Phase 1a/1b clinical trial of LP-284, and that will be presented by our very own Jianli Zhou on April 8, and it will focus on LP-284, which is a highly potent TP53 agnostic -- mutation agnostic DNA-damaging agent in refractory or relapsed lymphomas and other solid tumors. LP-284, as you know, we recently announced that we've dosed initial patients, and we expect to bring on many more sites and more patients in the coming quarter.

正如我之前在電話會議中提到的，上個季度，我們選擇了 AACR 2024 海報。它重點關注LP-284 的1a/1b 期臨床試驗，該試驗將由我們自己的周建利於4 月8 日介紹，它將重點關注LP-284，這是一種高效的TP53 不可知論藥物——突變不可知論藥物難治性或復發性淋巴瘤和其他實體腫瘤的 DNA 損傷劑。LP-284，如您所知，我們最近宣布我們已經對最初的患者進行了給藥，我們預計在下一季度引入更多的站點和更多的患者。

RADR continues to advance in size, scope, and capabilities and is also progressing, we believe, to becoming a standard for AI-driven drug development in oncology, both for early-stage development and later-stage patient biomarker and combination therapy identification. RADR has now surpassed over 60 billion oncology-focused data points and is projected to reach, well, over 100 billion, we believe, by the end of this year.

我們相信，RADR 在規模、範圍和能力方面不斷進步，並且正在成為腫瘤學領域人工智慧驅動藥物開發的標準，無論是早期開發還是後期患者生物標記和聯合治療識別。RADR 目前已超過 600 億個以腫瘤學為中心的數據點，我們相信，預計到今年年底將達到超過 1000 億個。

The scope of RADR's data has broadened with the strategic focus on additional classes of compounds, including antibodies, checkpoint inhibitors, and DNA-damaging agents. Additionally, data from clinical studies such as those being obtained from liquid biopsy and data from preclinical combination studies that aim to define drug interaction and optimal dosage are being incorporated into the data points and the datasets to power RADR. These data points, the associate advancements in automation, along with algorithms and code, comprised of functional module in our platform. And we believe that we'll have over eight of these modules and all will help us advance and improve the speed, the precision, and the efficiency of RADR's drug development, kind of copiloting capabilities.

隨著策略重點放在其他類別的化合物上，包括抗體、檢查點抑制劑和 DNA 損傷劑，RADR 的數據範圍已經擴大。此外，來自臨床研究的數據（例如從液體活檢獲得的數據）和旨在定義藥物交互作用和最佳劑量的臨床前組合研究的數據正在被納入數據點和數據集中，為 RADR 提供支援。這些數據點、自動化的相關進步以及演算法和程式碼，由我們平台中的功能模組組成。我們相信，我們將擁有超過八個這樣的模組，所有這些模組都將幫助我們推進和提高 RADR 藥物開發的速度、精度和效率，以及某種副駕駛能力。

During the second quarter, we'll host a webinar Wednesday, discussing the near-term roadmap and the use cases for the AI platform, RADR, which we believe, again, is the largest, most focused for oncology drug development.

在第二季度，我們將在周三舉辦一次網路研討會，討論人工智慧平台 RADR 的近期路線圖和用例，我們再次相信，這是最大、最關注的腫瘤藥物開發平台。

So 2023 was a pivotal year for us. Our insights are now entering into patient clinical trials. They started their journey to becoming meaningful therapies in cancer. Our collective efforts and dedication and fostered a transformational shift for our company, setting us on an exciting trajectory towards the future, where we're improving the lives of cancer patients with effective and more economically generated treatment options.

因此，2023 年對我們來說是關鍵的一年。我們的見解現在正在進入患者臨床試驗。他們開始了成為有意義的癌症療法的旅程。我們的集體努力和奉獻精神促進了我們公司的轉型轉變，使我們走上了一條通往未來的令人興奮的軌道，我們正在透過有效且更經濟的治療方案來改善癌症患者的生活。

For 2024, we have a lot of other exciting objectives. We expect 2024 to be a breakthrough year for Lantern and our programs, specifically, we have -- we'd like to share kind of our top 10 milestones.

對於 2024 年，我們還有許多其他令人興奮的目標。我們預計 2024 年將是 Lantern 和我們的計劃突破的一年，具體來說，我們希望分享我們的十大里程碑。

We want to advance and expand our Phase 1 clinical trial for LP-184. We expect to accelerate enrollment in LP-284 in non-Hodgkin's lymphoma and some other responsive cancers. We will expand enrollment of Harmonic trial into targeted sites in Asia, where the incidence of non-small-cell lung cancer and never smokers about three times higher.

我們希望推進並擴大 LP-184 的 1 期臨床試驗。我們預計將加速 LP-284 治療非何杰金氏淋巴瘤和其他一些反應性癌症的入組。我們將把 Harmonic 試驗的招募範圍擴大到亞洲的目標地點，那裡的非小細胞肺癌和從不吸菸者的發生率大約高出三倍。

We're going to explore licensing and partnership capabilities -- opportunities with biopharma companies, expand RADR's platform to over 100 billion data points, and develop additional collaborations with biopharma companies, both large and small that we'll be announcing. We also expect to progress Starlight Therapeutics towards a Phase 1b/2 adult clinical trial and perhaps a Phase 1 pediatric trial by early next year or the end of this year.

我們將探索許可和合作能力——與生物製藥公司的機會，將 RADR 的平台擴展到超過 1000 億個數據點，並與我們將宣布的大大小小的生物製藥公司進行更多合作。我們也預期在明年初或今年底前將 Starlight Therapeutics 推向 1b/2 期成人臨床試驗，或許還有 1 期兒科試驗。

We'll also -- we'll further -- our ADC preclinical into IND development to support future partnering our Phase 1 launch. We have developed combination programs for all three of our drugs with existing approved drugs. That is a big area of focus for our platform and for additional trials over the next couple of years. We plan on growing and maturing our clinical operations capabilities and then most importantly, continue our disciplined, fiscal, and financial management.

我們還將 - 我們將進一步 - 我們的 ADC 臨床前進入 IND 開發，以支持未來與我們的第一階段啟動合作。我們已經為我們的所有三種藥物與現有批准的藥物開發了聯合方案。這是我們平台以及未來幾年更多試驗的重點領域。我們計劃發展和完善我們的臨床營運能力，最重要的是，繼續我們的紀律、財務和財務管理。

So wanted to share those, and we'll be providing updates routinely, both through webinars, roadshows, investor meetings, and in press releases. We believe this is a great year to keep on communications with all of our interested parties very high.

所以想分享這些，我們將透過網路研討會、路演、投資者會議和新聞稿定期提供更新。我們相信今年是與所有感興趣的各方保持高度溝通的美好一年。

And in closing, I also want to express my gratitude to our team, our partners, and our stakeholders for their unwavering support. Together, we are really leading the way toward a brighter and better future in oncology and solving real-world problems with proprietary, high-value AI solutions that enable rapid development of genomically targeted therapies and at the same time, putting a path in place to alter the cost and timeline in drug discovery. And we think this places us at the forefront of a new era of development in medicine, well, I'd like to call the emergence of a golden age in medicine due to AI.

最後，我也要對我們的團隊、合作夥伴和利害關係人的堅定支持表示感謝。我們一起真正引領腫瘤學走向更光明、更美好的未來，並透過專有的、高價值的人工智慧解決方案解決現實世界的問題，這些解決方案能夠快速開發基因組標靶療法，同時為改變藥物發現的成本和時間表。我們認為這使我們處於醫學發展新時代的前沿，我想將人工智慧稱為醫學黃金時代的出現。

With that, I'd like to now open the call for any questions or clarifications.

至此，我現在想打開電話詢問任何問題或澄清。

First question from John. A great question. ADCs have been an important area of acquisition over the last year, and I have heard broadly that in general M&A conversations have picked up for life sciences, have you observed continued interest in ADCs from larger biopharmas?

第一個問題來自約翰。這是一個很好的問題。去年，ADC 一直是收購的重要領域，我廣泛聽說生命科學領域的併購對話有所回升，您是否觀察到大型生物製藥公司對 ADC 的持續興趣？

I would answer that question. Yes, John, we have seen interest from, actually, small, mid-size, and larger biopharmas in ADC, specifically on our cryptophycin ADC. Again, it's early a lot of the M&A deals that we saw earlier this year and some in last year were in later stage, ADC companies, many of them actually were already clinical. So it is exciting. There is, I think, not a lot of really unique assets in the ADCs. I mean, I think most the payloads, almost 70%-plus. The payloads are all the same. The designs tend to be very clumped together in terms of the category. So I think of the novel target and plus, perhaps, a novel payload with superior potency, especially in areas that are overlooked could be have a lot of interest. So I think if you follow all the data as opposed to a me-too approach, I think you're going to create something valuable. Great question. I mean, as we get more data, we will explore licensing or partnering the asset out as early as possible.

我會回答這個問題。是的，John，實際上，我們已經看到小型、中型和大型生物製藥公司對 ADC 感興趣，特別是對我們的 Cryptophycin ADC。再說一次，我們今年早些時候看到的許多併購交易都還處於早期階段，去年的一些併購交易還處於後期階段，ADC 公司，其中許多實際上已經進入臨床階段。所以這很令人興奮。我認為 ADC 中真正獨特的資產並不多。我的意思是，我認為大部分有效載荷，幾乎 70% 以上。有效負載都是相同的。就類別而言，設計往往非常擁擠。因此，我想到了新的目標，也許還有一種具有卓越效力的新有效載荷，尤其是在被忽視的領域，可能會引起人們很大的興趣。因此，我認為，如果您遵循所有數據而不是效仿方法，我認為您將創造出有價值的東西。很好的問題。我的意思是，隨著我們獲得更多數據，我們將儘早探索資產許可或合作。

Sure. We have another question from John. We hinted about a RADR platform moving now from 5 billion, I guess, couple of years ago to 60 billion. So the -- we're going to have a more detailed platform, kind of view day, but the platform now has begun evolving to the point where it can begin curating -- ingesting and curating data on its own. So we've gone through the process of what we call campaigns. So we have data ingestion campaigns where we -- initially, we're doing this manually. And as we created kind of roadmaps or templates for how to ingest the data and what the data structures are like. What the issues are like with, of course, now train the AI to begin doing this for us.

當然。約翰還有一個問題。我們暗示 RADR 平台現在的規模將從幾年前的 50 億增加到 600 億。因此，我們將有一個更詳細的平台，某種觀點日，但該平台現在已經開始發展到可以開始自行管理資料的程度。我們已經完成了所謂的行銷活動的過程。因此，我們進行資料攝取活動，最初，我們手動執行此操作。我們創建了一些路線圖或範本來說明如何攝取資料以及資料結構是什麼樣的。當然，問題是什麼，現在訓練人工智慧開始為我們做這件事。

The AI now has learned a lot of the common datasets and common data conventions and common meta tagging. And so the AI is beginning to do the data ingestion. That's a big platform evolution. The AI is also beginning to prioritize all the algorithms and generate new algorithms. So our team can now take a step back as the platform basically starts growing in and on itself. And so we've also now started a process to do what we called engineered data, data that we're extracting from other data that people don't have access to. And so this kind of level 2 data actually is going to be making a lot of insight creation, even more efficient and even more proprietary. And we'll talk about that when we talk about our platform. But yes, the platform has grown. It's kind of a different beast now than it was even 1.5 years ago and will continue to evolve.

人工智慧現在已經學習了許多常見的資料集、常見的資料約定和常見的元標記。因此人工智慧開始進行資料攝取。這是一個巨大的平台演進。人工智慧也開始優先考慮所有演算法並產生新演算法。因此，我們的團隊現在可以退後一步，因為該平台基本上開始自行發展。因此，我們現在也啟動了一個流程來處理我們所謂的工程數據，即我們從人們無法存取的其他數據中提取的數據。因此，這種 2 級數據實際上會產生大量的洞察力，甚至更有效率、更專有。當我們談論我們的平台時，我們會談論這一點。但是，是的，這個平台已經成長了。與 1.5 年前相比，現在它已經是一種不同的野獸，並將繼續發展。

Another question. This about our buyback and plans for that. So David, do you want to talk a little bit about what we did last year?

另一個問題。這是關於我們的回購和計劃。大衛，你想談談我們去年做了什麼嗎？

Sure. Yes. This was not a -- it was not a buyback program. It was purchased from two holders, but we felt this was in the best interest of the company, accretive to shareholders, and made sense. We purchased a 145,348 shares at $3.44 a share for an aggregate of right around 500,000. And as we described earlier in the call, it's reduced our shares outstanding, which we believe is also beneficial to our holders.

當然。是的。這不是回購計劃。它是從兩個持有者手中購買的，但我們認為這符合公司的最佳利益，有利於股東，而且是有道理的。我們以每股 3.44 美元的價格購買了 145,348 股，總計約 500,000 股。正如我們之前在電話會議中所描述的，它減少了我們的流通股，我們相信這對我們的持有者也有利。

Thanks, David. Another question. How do you decide about the timing for selecting a narrower Phase 2 indication?

謝謝，大衛。另一個問題。您如何決定選擇較窄的第二階段適應症的時機？

I think, again, we allow data to guide the decision process. So as we get the data from the first set of patients, which is about 35 patients in the Phase 1a, may go slightly over that. We'll see what the data suggests. We certainly have ideas based on our in silico findings and our in vivo work and our animal model work. And so hopefully, it'll support or validate or nullify, but data is everything. So we'll see what the data suggests about the narrow indications.

我再次認為，我們讓數據來引導決策過程。因此，當我們從第一組患者（即 1a 期患者中的約 35 名患者）獲得數據時，可能會稍微超出這個數字。我們將看看數據顯示什麼。我們當然有基於我們的電腦研究結果、體內工作和動物模型工作的想法。希望它能夠支援、驗證或無效，但數據就是一切。因此，我們將看看數據對狹窄適應症有何啟示。

We think clearly, we see that tumors with DNA-damaged repair deficiency seem to be very sensitive. So we think that it will probably be one of the indications and it may be a pan-tumor indication. We've also seen that tumors have high levels of PTGR1 above a certain threshold, roughly around 4.2 times of what's in a normal cell also tend to be very sensitive. So if this continues to hold up throughout the trial, those are two very good kind of hallmarks of a characteristic for the indication.

我們想清楚了，我們看到DNA損傷修復缺陷的腫瘤似乎非常敏感。所以我們認為它可能是適應症之一，而且可能是泛腫瘤適應症。我們也發現，腫瘤的 PTGR1 水平很高，高於某個閾值，大約是正常細胞的 4.2 倍左右，而且腫瘤也非常敏感。因此，如果在整個試驗過程中這種情況持續存在，那麼這些都是該適應症特徵的兩個非常好的標誌。

We may go after some targeted indications if we see that things like pancreatic and triple-negative breast cancer are even more sensitive. And we see that there's a clear need, and we think we can do a focused trial. They'll, obviously, bubble up to the top. So we'll see what the data suggests, and then we'll take a look at commercially what is the most efficient way to bring the drug to market.

如果我們發現胰臟癌和三陰性乳癌等疾病更加敏感，我們可能會尋求一些有針對性的適應症。我們看到有明確的需求，我們認為我們可以進行有針對性的試驗。顯然，它們會冒泡到頂部。因此，我們將看看數據顯示什麼，然後我們將研究商業上將藥物推向市場的最有效方法。

Next question is, do we intend to create further value by creating other companies?

下一個問題是，我們是否打算透過創造其他公司來創造更多價值？

Yeah, that's a great question. We think Starlight is very unique because there's really no company that has focused 100% on a breakthrough new molecule for CNS indications. That's the reason we're able to get a lot of interest around it. We've had pharmas reach out about it. We've had biotechs reach out about it. The drug has very good history in terms of its ability to be proven mechanistic, manner in which you can kill GBM cells, which is an alkylating agent.

是的，這是一個很好的問題。我們認為 Starlight 非常獨特，因為確實沒有一家公司 100% 專注於 CNS 適應症的突破性新分子。這就是我們能夠引起人們廣泛興趣的原因。我們已讓製藥公司聯繫此事。我們已經讓生物技術人員伸出援手。該藥物在其機制方面具有悠久的歷史，它可以殺死 GBM 細胞（一種烷化劑）。

In fact, the only process seemed to really work to kill off our alkylators like nitrosoureas and TMZ. I mean, everything else has had a middling to no effect. So we're in a good drug class. We're in a class that has a history of working. We're in a drug that seems to prefer cancer cells or any other type of cell. It seems to be much more bioavailable on, and it seems to be have better a blood-brain barrier penetrability than TMZ. It seems to be agnostic to MGMT. And it seems to work in several other brain cancers.

事實上，唯一的過程似乎真正有效地殺死我們的烷化劑，如亞硝基脲和TMZ。我的意思是，其他一切都產生了中等甚至沒有影響。所以我們處於一個很好的藥物類別。我們所在的班級有工作歷史。我們的藥物似乎更喜歡癌細胞或任何其他類型的細胞。它似乎比 TMZ 具有更高的生物利用度，並且似乎具有更好的血腦屏障滲透性。這對 MGMT 來說似乎是不可知的。它似乎對其他幾種腦癌也有效。

So I think it was a very unique opportunity. We had to AI insights, what a unique molecule. We're able to find not just one indication, but a family of kind of indications. And so, it was really paramount that we launched this effort on its own, get it done further and deeper.

所以我認為這是一個非常獨特的機會。我們必須了解人工智慧，這是一個多麼獨特的分子。我們不僅能找到一個跡象，還能找到一系列跡象。因此，至關重要的是，我們自己發起了這項工作，並進一步深入完成它。

If we see opportunities like that, we'll presume, we have to presume. I mean, I think ADCs could be like that. What we're seeing in terms of the early efforts, both on our antibody drug conjugate, but also another very exciting space we're looking at are fragments, fragment bodies. And we can actually get even more precision against the antigen or the target of interested what we call FDCs, fragment drug conjugates. And we've begun some very early exploratory work in that area with the cryptophycin and other picomolar agents.

如果我們看到這樣的機會，我們會假設，我們必須假設。我的意思是，我認為 ADC 可能就是這樣。我們所看到的早期努力，無論是在我們的抗體藥物綴合物上，還是我們正在關注的另一個非常令人興奮的領域是片段、片段體。實際上，我們可以更精確地針對抗原或感興趣的目標（我們稱之為 FDC，片段藥物綴合物）。我們已經開始在該領域使用隱藻素和其他皮摩爾藥劑進行一些非常早期的探索性工作。

So again, we're trying to use the ADC module that we've created, define targets, and then find something unique in those targets and credit classify both late-stage existing antibodies, but also some early stage, where, perhaps, we can make the process compressed and cheaper. And that fragment -- FDCs can hold that future. And then we're also trying to find the right agents that give us the right kind of DAR and improvement in cure rates. Like we said, the cryptophycin versus the MMAEs.

因此，我們再次嘗試使用我們創建的 ADC 模組，定義目標，然後在這些目標中找到一些獨特的東西，並對後期現有抗體進行信用分類，也對一些早期階段的抗體進行信用分類，也許，我們可以使製程壓縮並且更便宜。而那個片段——FDC 可以掌控這個未來。然後我們也試圖找到合適的藥物，為我們提供合適的 DAR 並提高治癒率。正如我們所說，隱藻素與 MMAE 的對比。

Another such type -- it's just a log, better cure rate on the cancer cells. So it's -- if we think we can hold it up in a small portfolio of indications, again, it could be, again, a very great spin on idea. We're partnering idea very early on.

另一種這樣的類型——它只是一個對數，更好的癌細胞治癒率。所以，如果我們認為我們可以將其保留在一小部分適應症中，那麼它可能會再次成為一個非常好的想法。我們很早就有了合作的想法。

The question is, our own business development opportunities.

問題是，我們自己的企業發展機會。

Yeah, so we're exploring business development opportunities in three categories. Again, I don't like to really talk about deals until deals are really done. I don't think there's any point in getting people excited about -- pharma industry, everyone talks to everyone. So yes, we're in discussions with a lot of different companies. It doesn't mean that there may or may not be a deal, but let me walk through our deal ideas that we have that we're working on.

是的，所以我們正在探索三個類別的業務發展機會。再說一次，在交易真正完成之前，我不喜歡真正談論交易。我認為讓人們興奮沒有任何意義——製藥業，每個人都與每個人交談。所以，是的，我們正在與許多不同的公司進行討論。這並不意味著可能會或可能不會達成協議，但讓我介紹一下我們正在研究的交易想法。

Number one, we do expect to announce deals with other biotech companies where they use our platform and we get certain rights to their to their drugs, their development efforts. So the part we're using our platform as currency to help those companies compress the timeline or decrease the risk or increase the ideas around that -- for their portfolio. And we get something in exchange for that, and that can be done with our platform.

第一，我們確實希望與其他生技公司達成交易，他們使用我們的平台，我們對他們的藥物和開發工作享有一定的權利。因此，我們使用我們的平台作為貨幣來幫助這些公司壓縮時間表或降低風險或增加圍繞其投資組合的想法。作為交換，我們得到了一些東西，這可以透過我們的平台來完成。

The second type of deal that we're beginning to explore and it's in fits and starts, but is with big tech companies. Big tech companies want to have unique platforms that they can offer in the cloud as a service to all their biopharma and academic and research groups. So now, imagine RADR, it can be taken into one of the big tech companies as a platform, and you can basically have RADR as a service. You can have any of these eight modules as a service: drug combination, blood-brain barrier penetrability drug, mechanism of action, hunting, ADC, design. So any of these modules, that's what we're trying to really create these unique modules. So again, that's very early.

我們開始探索的第二種交易是斷斷續續的，但是與大型科技公司進行的。大型科技公司希望擁有一個獨特的平台，可以在雲端為所有生物製藥以及學術和研究小組提供服務。所以現在，想像 RADR，它可以作為一個平台被納入一家大型科技公司，並且您基本上可以將 RADR 作為一項服務。您可以將這八個模組中的任何一個作為服務：藥物組合、血腦屏障滲透性藥物、作用機制、狩獵、ADC、設計。因此，這些模組中的任何一個都是我們真正嘗試創建這些獨特模組的。再說一遍，現在還很早。

And the third one is traditional partnership, licensing, selling of an asset or a program to Big Pharma. And I think the best way to excite Big Pharma is a data. So we'll power for the trials, we'll keep options open, and share the data and results like, again, we have 11, 12 programs now. So the likelihood of one of those, two of those programs even more getting licensed or spun out or sold off or partnered, I think continues to get higher and higher every quarter. Thank you for that question.

第三種是傳統的合作關係、許可、向大型製藥公司出售資產或專案。我認為讓大型製藥公司興奮的最佳方法是數據。因此，我們將為試驗提供動力，我們將保持開放的選擇，並分享數據和結果，就像我們現在有 11、12 個項目一樣。因此，我認為其中一個、其中兩個項目獲得許可、分拆、出售或合作的可能性每季都會越來越高。謝謝你提出這個問題。

So with that, I'd like to take a moment personally to thank everyone on our team for helping us prepare for these calls and prepare the information. We have got a lot of information out in the PR and also in the updated slides. We'll have a series of webinars throughout this year. We have the first three, or four actually, already kind of in program. And there's Webinar Wednesdays. I definitely urge you guys to join.

因此，我想親自花一點時間感謝我們團隊中的每個人幫助我們準備這些電話並準備資訊。我們在 PR 和更新的幻燈片中提供了大量資訊。今年我們將舉辦一系列網路研討會。我們已經有了前三個，或者實際上四個，已經在計劃中了。週三也有網路研討會。我絕對敦促你們加入。

We are very excited about what the future holds for us. We've got a number of trials that are ongoing, got a number of exciting programs that we can bring to market either spin-outs or partnered-out assets. And most importantly, the platform begins to grow. We're entering a new era of the AI platform. The AI platform now is beginning to grow itself. And more importantly, we are now creating new generative AI capabilities around molecular optimization and target selection, things that just didn't exist a year ago.

我們對我們的未來感到非常興奮。我們正在進行許多試驗，有許多令人興奮的項目，我們可以將它們推向市場，無論是分拆資產還是合作資產。最重要的是，該平台開始發展。我們正進入人工智慧平台的新時代。人工智慧平台現在開始自我發展。更重要的是，我們現在正在圍繞分子優化和目標選擇創建新的生成人工智慧功能，這些在一年前還不存在。

So on all fronts, we're growing. We've maintain fiscal discipline, and we've got significant amount of cash to continue executing our plan and reach milestones for partnering, selling, licensing on our portfolio.

所以在各方面，我們都在成長。我們一直保持財務紀律，並且擁有大量現金來繼續執行我們的計劃並達到我們投資組合的合作、銷售和許可方面的里程碑。

So thank you very much, and thank you for joining me this afternoon.

非常感謝你們，也感謝你們今天下午加入我的行列。

Thanks a lot.

多謝。

Thank you, David.

謝謝你，大衛。